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All publications in 2007
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Full regularization path for sparse principal component analysis
Alexandre D'aspremont, Francis R. Bach and Laurent E. Ghaoui
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Multiclass multiple kernel learning
Alexander Zien and Cheng S. Ong
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Transductive support vector machines for structured variables
Alexander Zien, Ulf Brefeld and Tobias Scheffer
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Dynamic hierarchical Markov random fields and their application to web data extraction
Jun Zhu, Zaiqing Nie, Bo Zhang and Ji-rong Wen
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


On the relation between multi-instance learning and semi-supervised learning
Zhi-hua Zhou and Jun-ming Xu
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Spectral clustering and transductive learning with multiple views
Dengyong Zhou and Christopher Burges
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Spectral feature selection for supervised and unsupervised learning
Zheng Zhao and Huan Liu
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


On the value of pairwise constraints in classification and consistency
Jian Zhang and Rong Yan
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Optimal dimensionality of metric space for classification
Wei Zhang, Xiangyang Xue, Zichen Sun, Yue-fei Guo and Hong Lu
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Maximum margin clustering made practical
Kai Zhang, Ivor W. Tsang and James T. Kwok
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Nonlinear independent component analysis with minimal nonlinear distortion
Kun Zhang and Laiwan Chan
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Conditional random fields for multi-agent reinforcement learning
Xinhua Zhang, Douglas Aberdeen and S.v.n. Vishwanathan
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Robust multi-task learning with {\it t}-processes
Shipeng Yu, Volker Tresp and Kai Yu
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


A fast linear separability test by projection of positive points on subspaces
A. P. Yogananda, M. N. Murty and Lakshmi Gopal
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Discriminant kernel and regularization parameter learning via semidefinite programming
Jieping Ye, Jianhui Chen and Shuiwang Ji
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Least squares linear discriminant analysis
Jieping Ye
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Asymptotic Bayesian generalization error when training and test distributions are different
Keisuke Yamazaki, Motoaki Kawanabe, Sumio Watanabe, Masashi Sugiyama and Klaus-robert Müller
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Map building without localization by dimensionality reduction techniques
Takehisa Yairi
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


The matrix stick-breaking process for flexible multi-task learning
Ya Xue, David B. Dunson and Lawrence Carin
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Modeling changing dependency structure in multivariate time series
Xiang Xuan and Kevin P. Murphy
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


On learning linear ranking functions for beam search
Yuehua Xu and Alan Fern
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Local learning projections
Mingrui Wu, Kai Yu, Shipeng Yu and Bernhard Schölkopf
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Learning to combine distances for complex representations
Adam Woznica, Alexandros Kalousis and Melanie Hilario
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Beamforming using the relevance vector machine
David P. Wipf and Srikantan S. Nagarajan
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Multi-task reinforcement learning: a hierarchical Bayesian approach
Aaron Wilson, Alan Fern, Soumya Ray and Prasad Tadepalli
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


What is decreased by the max-sum arc consistency algorithm?
Tomás Werner
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Winnowing subspaces
Manfred K. Warmuth
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Hybrid huberized support vector machines for microarray classification
Li Wang, Ji Zhu and Hui Zou
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Dirichlet aggregation: unsupervised learning towards an optimal metric for proportional data
Hua-yan Wang, Hongbin Zha and Hong Qin
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


A kernel path algorithm for support vector machines
Gang Wang, Dit-yan Yeung and Frederick H. Lochovsky
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Transductive regression piloted by inter-manifold relations
Huan Wang, Shuicheng Yan, Thomas S. Huang, Jianzhuang Liu and Xiaoou Tang
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


On learning with dissimilarity functions
Liwei Wang, Cheng Yang and Jufu Feng
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Multifactor Gaussian process models for style-content separation
Jack M. Wang, David J. Fleet and Aaron Hertzmann
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Learning from interpretations: a rooted kernel for ordered hypergraphs
Gabriel Wachman and Roni Khardon
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Discriminative Gaussian process latent variable model for classification
Raquel Urtasun and Trevor Darrell
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Entire regularization paths for graph data
Koji Tsuda
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Simpler core vector machines with enclosing balls
Ivor W. Tsang, András Kocsor and James T. Kwok
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Approximate maximum margin algorithms with rules controlled by the number of mistakes
Petroula Tsampouka and John Shawe-taylor
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Classifying matrices with a spectral regularization
Ryota Tomioka and Kazuyuki Aihara
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Incremental Bayesian networks for structure prediction
Ivan Titov and James Henderson
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Cross-domain transfer for reinforcement learning
Matthew E. Taylor and Peter Stone
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Piecewise pseudolikelihood for efficient training of conditional random fields
Charles A. Sutton and Andrew Mccallum
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


On the role of tracking in stationary environments
Richard S. Sutton, Anna Koop and David Silver
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Robust mixtures in the presence of measurement errors
Jianyong Sun, Ata Kabán and Somak Raychaudhury
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


A kernel-based causal learning algorithm
Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf and Kenji Fukumizu
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Learning to solve game trees
David H. Stern, Ralf Herbrich and Thore Graepel
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Sparse eigen methods by D.C. programming
Bharath K. Sriperumbudur, David A. Torres and Gert Lanckriet
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Supervised feature selection via dependence estimation
Le Song, Alex J. Smola, Arthur Gretton, Karsten M. Borgwardt and Justin Bedo
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


A dependence maximization view of clustering
Le Song, Arthur Gretton, Karsten M. Borgwardt and Alex J. Smola
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Pegasos: Primal Estimated sub-GrAdient SOlver for SVM
Shai Shalev-shwartz, Yoram Singer and Nathan Srebro
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Sample compression bounds for decision trees
Mohak Shah
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Restricted Boltzmann machines for collaborative filtering
Ruslan Salakhutdinov, Andriy Mnih and Geoffrey E. Hinton
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Graph clustering with network structure indices
Matthew J. Rattigan, Marc E. Maier and David Jensen
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


More efficiency in multiple kernel learning
Alain Rakotomamonjy, Stéphane Canu, Yves Grandvalet and Francis R. Bach
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Online discovery of similarity mappings
Alexander Rakhlin, Jacob Abernethy and Peter L. Bartlett
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Self-taught learning: transfer learning from unlabeled data
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin Packer and Andrew Y. Ng
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Tracking value function dynamics to improve reinforcement learning with piecewise linear function approximation
Chee W. Phua and Robert Fitch
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Reinforcement learning by reward-weighted regression for operational space control
Jan R. Peters and Stefan Schaal
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Analyzing feature generation for value-function approximation
Ronald Parr, Christopher Painter-wakefield, Lihong Li and Michael L. Littman
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Learning for efficient retrieval of structured data with noisy queries
Charles Parker, Alan Fern and Prasad Tadepalli
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Multi-armed bandit problems with dependent arms
Sandeep Pandey, Deepayan Chakrabarti and Deepak Agarwal
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Learning state-action basis functions for hierarchical MDPs
Sarah Osentoski and Sridhar Mahadevan
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Regression on manifolds using kernel dimension reduction
Jens Nilsson, Fei Sha and Michael I. Jordan
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Multi-task learning for sequential data via iHMMs and the nested Dirichlet process
Kai Ni, Lawrence Carin and David B. Dunson
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Comparisons of sequence labeling algorithms and extensions
Nam Nguyen and Yunsong Guo
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Revisiting probabilistic models for clustering with pair-wise constraints
Blaine Nelson and Ira Cohen
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Unsupervised estimation for noisy-channel models
Markos Mylonakis, Khalil Sima'an and Rebecca Hwa
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Dimensionality reduction and generalization
Sofia Mosci, Lorenzo Rosasco and Alessandro Verri
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Fast and effective kernels for relational learning from texts
Alessandro Moschitti and Fabio M. Zanzotto
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Three new graphical models for statistical language modelling
Andriy Mnih and Geoffrey E. Hinton
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Mixtures of hierarchical topics with Pachinko allocation
David M. Mimno, Wei Li and Andrew Mccallum
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Bottom-up learning of Markov logic network structure
Lilyana Mihalkova and Raymond J. Mooney
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Linear and nonlinear generative probabilistic class models for shape contours
Graham Mcneill and Sethu Vijayakumar
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Asymmetric boosting
Hamed Masnadi-shirazi and Nuno Vasconcelos
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Automatic shaping and decomposition of reward functions
Bhaskara Marthi
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Simple, robust, scalable semi-supervised learning via expectation regularization
Gideon S. Mann and Andrew Mccallum
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Adaptive mesh compression in 3D computer graphics using multiscale manifold learning
Sridhar Mahadevan
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Discriminant analysis in correlation similarity measure space
Yong Ma, Shihong Lao, Erina Takikawa and Masato Kawade
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Relational clustering by symmetric convex coding
Bo Long, Zhongfei (. Zhang, Xiaoyun Wu and Philip S. Yu
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Trust region Newton methods for large-scale logistic regression
Chih-jen Lin, Ruby C. Weng and S. S. Keerthi
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Quadratically gated mixture of experts for incomplete data classification
Xuejun Liao, Hui Li and Lawrence Carin
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


A permutation-augmented sampler for DP mixture models
Percy Liang, Michael I. Jordan and Ben Taskar
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


A transductive framework of distance metric learning by spectral dimensionality reduction
Fuxin Li, Jian Yang and Jue Wang
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Large-scale RLSC learning without agony
Wenye Li, Kin-hong Lee and Kwong-sak Leung
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


A novel orthogonal NMF-based belief compression for POMDPs
Xin Li, William K. Cheung, Jiming Liu and Zhili Wu
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Support cluster machine
Bin Li, Mingmin Chi, Jianping Fan and Xiangyang Xue
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Scalable modeling of real graphs using Kronecker multiplication
Jure Leskovec and Christos Faloutsos
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Learning a meta-level prior for feature relevance from multiple related tasks
Su-in Lee, Vassil Chatalbashev, David Vickrey and Daphne Koller
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Hierarchical Gaussian process latent variable models
Neil D. Lawrence and Andrew J. Moore
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


An empirical evaluation of deep architectures on problems with many factors of variation
Hugo Larochelle, Dumitru Erhan, Aaron C. Courville, James Bergstra and Yoshua Bengio
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Online kernel PCA with entropic matrix updates
Dima Kuzmin and Manfred K. Warmuth
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


On one method of non-diagonal regularization in sparse Bayesian learning
Dmitry Kropotov and Dmitry Vetrov
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Nonmyopic active learning of Gaussian processes: an exploration-exploitation approach
Andreas Krause and Carlos Guestrin
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Kernelizing PLS, degrees of freedom, and efficient model selection
Nicole Krämer and Mikio L. Braun
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Statistical predicate invention
Stanley Kok and Pedro Domingos
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Local dependent components
Arto Klami and Samuel Kaski
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Infinite mixtures of trees
Sergey Kirshner and Padhraic Smyth
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


A recursive method for discriminative mixture learning
Minyoung Kim and Vladimir Pavlovic
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Neighbor search with global geometry: a minimax message passing algorithm
Kye-hyeon Kim and Seungjin Choi
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Most likely heteroscedastic Gaussian process regression
Kristian Kersting, Christian Plagemann, Patrick Pfaff and Wolfram Burgard
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Constructing basis functions from directed graphs for value function approximation
Jeffrey Johns and Sridhar Mahadevan
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Bayesian compressive sensing and projection optimization
Shihao Ji and Lawrence Carin
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Parameter learning for relational Bayesian networks
Manfred Jaeger
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Experimental perspectives on learning from imbalanced data
Jason V. Hulse, Taghi M. Khoshgoftaar and Amri Napolitano
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Learning nonparametric kernel matrices from pairwise constraints
Steven Hoi, Rong Jin and Michael R. Lyu
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Sparse probabilistic classifiers
Romain Hérault and Yves Grandvalet
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


A bound on the label complexity of agnostic active learning
Steve Hanneke
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Supervised clustering of streaming data for email batch detection
Peter Haider, Ulf Brefeld and Tobias Scheffer
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Efficient inference with cardinality-based clique potentials
Rahul Gupta, Ajit A. Diwan and Sunita Sarawagi
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Recovering temporally rewiring networks: a model-based approach
Fan Guo, Steve Hanneke, Wenjie Fu and Eric P. Xing
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Best of both: a hybridized centroid-medoid clustering heuristic
Nizar Grira and Michael E. Houle
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Exponentiated gradient algorithms for log-linear structured prediction
Amir Globerson, Terry Koo, Xavier Carreras and Michael Collins
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Bayesian actor-critic algorithms
Mohammad Ghavamzadeh and Yaakov Engel
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Gradient boosting for kernelized output spaces
Pierre Geurts, Louis Wehenkel and Florence D'alché-buc
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Robust non-linear dimensionality reduction using successive 1-dimensional Laplacian Eigenmaps
Samuel Gerber, Tolga Tasdizen and Ross T. Whitaker
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Combining online and offline knowledge in UCT
Sylvain Gelly and David Silver
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Manifold-adaptive dimension estimation
Amir M. Farahmand, Csaba Szepesvári and Jean-yves Audibert
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


CarpeDiem: an algorithm for the fast evaluation of SSL classifiers
Roberto Esposito and Daniele P. Radicioni
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Hierarchical maximum entropy density estimation
Miroslav Dudík, David M. Blei and Robert E. Schapire
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Non-isometric manifold learning: analysis and an algorithm
Piotr Dollár, Vincent Rabaud and Serge J. Belongie
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Adaptive dimension reduction using discriminant analysis and {\it K}-means clustering
Chris Ding and Tao Li
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Unsupervised prediction of citation influences
Laura Dietz, Steffen Bickel and Tobias Scheffer
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Percentile optimization in uncertain Markov decision processes with application to efficient exploration
Erick Delage and Shie Mannor
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Information-theoretic metric learning
Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit Sra and Inderjit S. Dhillon
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


An integrated approach to feature invention and model construction for drug activity prediction
Jesse Davis, V\'ıtor S. Costa, Soumya Ray and David Page
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Intractability and clustering with constraints
Ian Davidson and S. S. Ravi
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Boosting for transfer learning
Wenyuan Dai, Qiang Yang, Gui-rong Xue and Yong Yu
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Kernel selection forl semi-supervised kernel machines
Guang Dai and Dit-yan Yeung
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Magnitude-preserving ranking algorithms
Corinna Cortes, Mehryar Mohri and Ashish Rastogi
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Learning to compress images and videos
Li Cheng and S.v.n. Vishwanathan
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Minimum reference set based feature selection for small sample classifications
Xue-wen Chen and Jong C. Jeong
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Direct convex relaxations of sparse SVM
Antoni B. Chan, Nuno Vasconcelos and Gert Lanckriet
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Local similarity discriminant analysis
Luca Cazzanti and Maya R. Gupta
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Feature selection in a kernel space
Bin Cao, Dou Shen, Jian-tao Sun, Qiang Yang and Zheng Chen
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Learning to rank: from pairwise approach to listwise approach
Zhe Cao, Tao Qin, Tie-yan Liu, Ming-feng Tsai and Hang Li
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Cluster analysis of heterogeneous rank data
Ludwig M. Busse, Peter Orbanz and Joachim M. Buhmann
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Multiple instance learning for sparse positive bags
Razvan C. Bunescu and Raymond J. Mooney
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Efficiently computing minimax expected-size confidence regions
Brent Bryan, H. B. Mcmahan, Chad M. Schafer and Jeff G. Schneider
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Solving multiclass support vector machines with LaRank
Antoine Bordes, Léon Bottou, Patrick Gallinari and Jason Weston
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Discriminative learning for differing training and test distributions
Steffen Bickel, Michael Brückner and Tobias Scheffer
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Structural alignment based kernels for protein structure classification
Sourangshu Bhattacharya, Chiranjib Bhattacharyya and Nagasuma Chandra
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Learning distance function by coding similarity
Aharon Bar-hillel and Daphna Weinshall
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Focused crawling with scalable ordinal regression solvers
Rashmin Babaria, J. S. Nath, S. Krishnan, K. R. Sivaramakrishnan, Chiranjib Bhattacharyya and M. N. Murty
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


The rendezvous algorithm: multiclass semi-supervised learning with Markov random walks
Arik Azran
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Multiclass core vector machine
S. Asharaf, M. N. Murty and Shirish K. Shevade
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Scalable training of L$^{\mbox{1}}$-regularized log-linear models
Galen Andrew and Jianfeng Gao
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Two-view feature generation model for semi-supervised learning
Rie K. Ando and Tong Zhang
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Uncovering shared structures in multiclass classification
Yonatan Amit, Michael Fink, Nathan Srebro and Shimon Ullman
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Quantum clustering algorithms
Esma A\"ımeur, Gilles Brassard and Sébastien Gambs
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Learning random walks to rank nodes in graphs
Alekh Agarwal and Soumen Chakrabarti
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Stagewise Lasso
Peng Zhao and Bin Yu
Journal of Machine Learning Research, 2007


Learnability of Gaussians with Flexible Variances
Yiming Ying and Ding-xuan Zhou
Journal of Machine Learning Research, 2007


Multi-Task Learning for Classification with Dirichlet Process Priors
Ya Xue, Xuejun Liao, Lawrence Carin and Balaji Krishnapuram
Journal of Machine Learning Research, 2007


Refinable Kernels
Yuesheng Xu and Haizhang Zhang
Journal of Machine Learning Research, 2007


Large Margin Semi-supervised Learning
Junhui Wang and Xiaotong Shen
Journal of Machine Learning Research, 2007


Margin Trees for High-dimensional Classification
Robert Tibshirani and Trevor Hastie
Journal of Machine Learning Research, 2007


On the Consistency of Multiclass Classification Methods
Ambuj Tewari and Peter L. Bartlett
Journal of Machine Learning Research, 2007


A Unified Continuous Optimization Framework for Center-Based Clustering Methods
Marc Teboulle
Journal of Machine Learning Research, 2007


Transfer Learning via Inter-Task Mappings for Temporal Difference Learning
Matthew E. Taylor, Peter Stone and Yaxin Liu
Journal of Machine Learning Research, 2007


Distances between Data Sets Based on Summary Statistics
Nikolaj Tatti
Journal of Machine Learning Research, 2007


Undercomplete Blind Subspace Deconvolution
Zoltán Szabó, Barnabás Póczos and András Lörincz
Journal of Machine Learning Research, 2007


Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data
Charles A. Sutton, Andrew Mccallum and Khashayar Rohanimanesh
Journal of Machine Learning Research, 2007


Covariate Shift Adaptation by Importance Weighted Cross Validation
Masashi Sugiyama, Matthias Krauledat and Klaus-robert Müller
Journal of Machine Learning Research, 2007


Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis
Masashi Sugiyama
Journal of Machine Learning Research, 2007


Bayesian Quadratic Discriminant Analysis
Santosh Srivastava, Maya R. Gupta and Bela A. Frigyik
Journal of Machine Learning Research, 2007


The Need for Open Source Software in Machine Learning
Sören Sonnenburg, Mikio L. Braun, Cheng S. Ong, Samy Bengio, Léon Bottou, Geoffrey Holmes, Yann Lecun, Klaus-robert Müller, Fernando Pereira, Carl E. Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Pascal Vincent, Jason Weston, Robert C. Williamson and Alex J. Smola
Journal of Machine Learning Research, 2007


Handling Missing Values when Applying Classification Models
Maytal Saar-tsechansky and Foster J. Provost
Journal of Machine Learning Research, 2007


Generalization Error Bounds in Semi-supervised Classification Under the Cluster Assumption
Philippe Rigollet
Journal of Machine Learning Research, 2007


Value Regularization and Fenchel Duality
Ryan M. Rifkin and Ross A. Lippert
Journal of Machine Learning Research, 2007


Learning Equivariant Functions with Matrix Valued Kernels
Marco Reisert and Hans Burkhardt
Journal of Machine Learning Research, 2007


Building Blocks for Variational Bayesian Learning of Latent Variable Models
Tapani Raiko, Harri Valpola, Markus Harva and Juha Karhunen
Journal of Machine Learning Research, 2007


Characterizing the Function Space for Bayesian Kernel Models
Natesh S. Pillai, Qiang Wu, Feng Liang, Sayan Mukherjee and Robert L. Wolpert
Journal of Machine Learning Research, 2007


Penalized Model-Based Clustering with Application to Variable Selection
Wei Pan and Xiaotong Shen
Journal of Machine Learning Research, 2007


Infinitely Imbalanced Logistic Regression
Art B. Owen
Journal of Machine Learning Research, 2007


Synergistic Face Detection and Pose Estimation with Energy-Based Models
Margarita Osadchy, Yann Lecun and Matthew L. Miller
Journal of Machine Learning Research, 2007


Learning in Environments with Unknown Dynamics: Towards more Robust Concept Learners
Marlon N\'uñez, Ra\'ul Fidalgo and Rafael Morales
Journal of Machine Learning Research, 2007


Consistent Feature Selection for Pattern Recognition in Polynomial Time
Roland Nilsson, José M. Peña, Johan Björkegren and Jesper Tegnér
Journal of Machine Learning Research, 2007


Relational Dependency Networks
Jennifer Neville and David Jensen
Journal of Machine Learning Research, 2007


Neural characterization in partially observed populations of spiking neurons
Jonathan W. Pillow and Peter E. Latham
Advances in Neural Information Processing Systems 20, 2007


Combined discriminative and generative articulated pose and non-rigid shape estimation
Leonid Sigal, Alexandru Balan and Michael J. Black
Advances in Neural Information Processing Systems 20, 2007


CPR for CSPs: A Probabilistic Relaxation of Constraint Propagation
Luis E. Ortiz
Advances in Neural Information Processing Systems 20, 2007


Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion
J. Z. Kolter, Pieter Abbeel and Andrew Y. Ng
Advances in Neural Information Processing Systems 20, 2007


Invariant Common Spatial Patterns: Alleviating Nonstationarities in Brain-Computer Interfacing
Benjamin Blankertz, Motoaki Kawanabe, Ryota Tomioka, Friederike Hohlefeld, Klaus-robert Müller and Vadim V. Nikulin
Advances in Neural Information Processing Systems 20, 2007


Robust Regression with Twinned Gaussian Processes
Andrew Naish-guzman and Sean Holden
Advances in Neural Information Processing Systems 20, 2007


A New View of Automatic Relevance Determination
David P. Wipf and Srikantan S. Nagarajan
Advances in Neural Information Processing Systems 20, 2007


A Bayesian LDA-based model for semi-supervised part-of-speech tagging
Kristina Toutanova and Mark Johnson
Advances in Neural Information Processing Systems 20, 2007


Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods
Alessandro Lazaric, Marcello Restelli and Andrea Bonarini
Advances in Neural Information Processing Systems 20, 2007


Modeling image patches with a directed hierarchy of Markov random fields
Simon Osindero and Geoffrey E. Hinton
Advances in Neural Information Processing Systems 20, 2007


Cluster Stability for Finite Samples
Ohad Shamir and Naftali Tishby
Advances in Neural Information Processing Systems 20, 2007


A Game-Theoretic Approach to Apprenticeship Learning
Umar Syed and Robert E. Schapire
Advances in Neural Information Processing Systems 20, 2007


Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes
Geoffrey E. Hinton and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 20, 2007


Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations
Amir Globerson and Tommi S. Jaakkola
Advances in Neural Information Processing Systems 20, 2007


Sparse deep belief net model for visual area V2
Honglak Lee, Chaitanya Ekanadham and Andrew Y. Ng
Advances in Neural Information Processing Systems 20, 2007


TrueSkill Through Time: Revisiting the History of Chess
Pierre Dangauthier, Ralf Herbrich, Tom Minka and Thore Graepel
Advances in Neural Information Processing Systems 20, 2007


Gaussian Process Models for Link Analysis and Transfer Learning
Kai Yu and Wei Chu
Advances in Neural Information Processing Systems 20, 2007


Hippocampal Contributions to Control: The Third Way
Máté Lengyel and Peter Dayan
Advances in Neural Information Processing Systems 20, 2007


Learning the 2-D Topology of Images
Nicolas L. Roux, Yoshua Bengio, Pascal Lamblin, Marc Joliveau and Balázs Kégl
Advances in Neural Information Processing Systems 20, 2007


Message Passing for Max-weight Independent Set
Sujay Sanghavi, Devavrat Shah and Alan S. Willsky
Advances in Neural Information Processing Systems 20, 2007


Discriminative Batch Mode Active Learning
Yuhong Guo and Dale Schuurmans
Advances in Neural Information Processing Systems 20, 2007


Regulator Discovery from Gene Expression Time Series of Malaria Parasites: a Hierachical Approach
José M. Hernández-lobato, Tjeerd Dijkstra and Tom Heskes
Advances in Neural Information Processing Systems 20, 2007


Expectation Maximization and Posterior Constraints
Kuzman Ganchev, Ben Taskar and João Gama
Advances in Neural Information Processing Systems 20, 2007


Fitted Q-iteration in continuous action-space MDPs
András Antos, Csaba Szepesvári and Rémi Munos
Advances in Neural Information Processing Systems 20, 2007


Locality and low-dimensions in the prediction of natural experience from fMRI
Francois Meyer and Greg Stephens
Advances in Neural Information Processing Systems 20, 2007


Congruence between model and human attention reveals unique signatures of critical visual events
Robert Peters and Laurent Itti
Advances in Neural Information Processing Systems 20, 2007


Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning
Gerald Tesauro, Rajarshi Das, Hoi Chan, Jeffrey Kephart, David Levine, Freeman Rawson and Charles Lefurgy
Advances in Neural Information Processing Systems 20, 2007


Linear programming analysis of loopy belief propagation for weighted matching
Sujay Sanghavi, Dmitry Malioutov and Alan S. Willsky
Advances in Neural Information Processing Systems 20, 2007


Active Preference Learning with Discrete Choice Data
Brochu Eric, Nando D. Freitas and Abhijeet Ghosh
Advances in Neural Information Processing Systems 20, 2007


Predictive Matrix-Variate t Models
Shenghuo Zhu, Kai Yu and Yihong Gong
Advances in Neural Information Processing Systems 20, 2007


Unconstrained On-line Handwriting Recognition with Recurrent Neural Networks
Alex Graves, Marcus Liwicki, Horst Bunke, Jürgen Schmidhuber and Santiago Fernández
Advances in Neural Information Processing Systems 20, 2007


Supervised Topic Models
Jon D. Mcauliffe and David M. Blei
Advances in Neural Information Processing Systems 20, 2007


Automatic Generation of Social Tags for Music Recommendation
Douglas Eck, Paul Lamere, Thierry Bertin-mahieux and Stephen Green
Advances in Neural Information Processing Systems 20, 2007


Boosting Algorithms for Maximizing the Soft Margin
Gunnar Rätsch, Manfred K. Warmuth and Karen A. Glocer
Advances in Neural Information Processing Systems 20, 2007


A Probabilistic Approach to Language Change
Alexandre Bouchard-côté, Percy Liang, Dan Klein and Thomas L. Griffiths
Advances in Neural Information Processing Systems 20, 2007


Privacy-Preserving Belief Propagation and Sampling
Michael Kearns, Jinsong Tan and Jennifer Wortman
Advances in Neural Information Processing Systems 20, 2007


A Bayesian Framework for Cross-Situational Word-Learning
Noah Goodman, Joshua B. Tenenbaum and Michael J. Black
Advances in Neural Information Processing Systems 20, 2007


The discriminant center-surround hypothesis for bottom-up saliency
Dashan Gao, Vijay Mahadevan and Nuno Vasconcelos
Advances in Neural Information Processing Systems 20, 2007


DIFFRAC: a discriminative and flexible framework for clustering
Francis R. Bach and Za\"ıd Harchaoui
Advances in Neural Information Processing Systems 20, 2007


Bayes-Adaptive POMDPs
Stephane Ross, Brahim Chaib-draa and Joelle Pineau
Advances in Neural Information Processing Systems 20, 2007


Fast and Scalable Training of Semi-Supervised CRFs with Application to Activity Recognition
Maryam Mahdaviani and Tanzeem Choudhury
Advances in Neural Information Processing Systems 20, 2007


Efficient Inference for Distributions on Permutations
Jonathan Huang, Carlos Guestrin and Leonidas Guibas
Advances in Neural Information Processing Systems 20, 2007


Fast Variational Inference for Large-scale Internet Diagnosis
Emre Kiciman, David Maltz and John C. Platt
Advances in Neural Information Processing Systems 20, 2007


Non-parametric Modeling of Partially Ranked Data
Guy Lebanon and Yi Mao
Advances in Neural Information Processing Systems 20, 2007


McRank: Learning to Rank Using Multiple Classification and Gradient Boosting
Ping Li, Qiang Wu and Christopher J. Burges
Advances in Neural Information Processing Systems 20, 2007


The Infinite Markov Model
Daichi Mochihashi and Eiichiro Sumita
Advances in Neural Information Processing Systems 20, 2007


Random Features for Large-Scale Kernel Machines
Ali Rahimi and Benjamin Recht
Advances in Neural Information Processing Systems 20, 2007


Cooled and Relaxed Survey Propagation for MRFs
Hai L. Chieu, Wee S. Lee and Yee W. Teh
Advances in Neural Information Processing Systems 20, 2007


New Outer Bounds on the Marginal Polytope
David Sontag and Tommi S. Jaakkola
Advances in Neural Information Processing Systems 20, 2007


Augmented Functional Time Series Representation and Forecasting with Gaussian Processes
Nicolas Chapados and Yoshua Bengio
Advances in Neural Information Processing Systems 20, 2007


Structured Learning with Approximate Inference
Alex Kulesza and Fernando Pereira
Advances in Neural Information Processing Systems 20, 2007


Computing Robust Counter-Strategies
Michael Johanson, Martin Zinkevich and Michael Bowling
Advances in Neural Information Processing Systems 20, 2007


Subspace-Based Face Recognition in Analog VLSI
Gonzalo Carvajal, Waldo Valenzuela and Miguel Figueroa
Advances in Neural Information Processing Systems 20, 2007


Unsupervised Feature Selection for Accurate Recommendation of High-Dimensional Image Data
Sabri Boutemedjet, Djemel Ziou and Nizar Bouguila
Advances in Neural Information Processing Systems 20, 2007


Blind channel identification for speech dereverberation using l1-norm sparse learning
Yuanqing Lin, Jingdong Chen, Youngmoo Kim and Daniel D. Lee
Advances in Neural Information Processing Systems 20, 2007


The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information
John Langford and Tong Zhang
Advances in Neural Information Processing Systems 20, 2007


Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization
Xuanlong Nguyen, Martin J. Wainwright and Michael I. Jordan
Advances in Neural Information Processing Systems 20, 2007


Local Algorithms for Approximate Inference in Minor-Excluded Graphs
Kyomin Jung and Devavrat Shah
Advances in Neural Information Processing Systems 20, 2007


An Analysis of Inference with the Universum
Olivier Chapelle, Alekh Agarwal, Fabian H. Sinz and Bernhard Schölkopf
Advances in Neural Information Processing Systems 20, 2007


Object Recognition by Scene Alignment
Bryan Russell, Antonio Torralba, Ce Liu, Rob Fergus and William T. Freeman
Advances in Neural Information Processing Systems 20, 2007


Second Order Bilinear Discriminant Analysis for single trial EEG analysis
Christoforos Christoforou, Paul Sajda and Lucas C. Parra
Advances in Neural Information Processing Systems 20, 2007


Collapsed Variational Inference for HDP
Yee W. Teh, Kenichi Kurihara and Max Welling
Advances in Neural Information Processing Systems 20, 2007


Bayesian Agglomerative Clustering with Coalescents
Yee W. Teh, Daniel J. Hsu and Hal Daume
Advances in Neural Information Processing Systems 20, 2007


The Price of Bandit Information for Online Optimization
Varsha Dani, Sham M. Kakade and Thomas P. Hayes
Advances in Neural Information Processing Systems 20, 2007


Catching Up Faster in Bayesian Model Selection and Model Averaging
Tim V. Erven, Steven D. Rooij and Peter Grünwald
Advances in Neural Information Processing Systems 20, 2007


Evaluating Search Engines by Modeling the Relationship Between Relevance and Clicks
Ben Carterette and Rosie Jones
Advances in Neural Information Processing Systems 20, 2007


Hidden Common Cause Relations in Relational Learning
Ricardo Silva, Wei Chu and Zoubin Ghahramani
Advances in Neural Information Processing Systems 20, 2007


A General Boosting Method and its Application to Learning Ranking Functions for Web Search
Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier Chapelle, Keke Chen and Gordon Sun
Advances in Neural Information Processing Systems 20, 2007


Discriminative K-means for Clustering
Jieping Ye, Zheng Zhao and Mingrui Wu
Advances in Neural Information Processing Systems 20, 2007


A Kernel Statistical Test of Independence
Arthur Gretton, Kenji Fukumizu, Choon H. Teo, Le Song, Bernhard Schölkopf and Alex J. Smola
Advances in Neural Information Processing Systems 20, 2007


The Tradeoffs of Large Scale Learning
Olivier Bousquet and Léon Bottou
Advances in Neural Information Processing Systems 20, 2007


The Distribution Family of Similarity Distances
Gertjan Burghouts, Arnold Smeulders and Jan-mark Geusebroek
Advances in Neural Information Processing Systems 20, 2007


A configurable analog VLSI neural network with spiking neurons and self-regulating plastic synapses
Massimiliano Giulioni, Mario Pannunzi, Davide Badoni, Vittorio Dante and Paolo D. Giudice
Advances in Neural Information Processing Systems 20, 2007


Sequential Hypothesis Testing under Stochastic Deadlines
Peter Frazier and Angela J. Yu
Advances in Neural Information Processing Systems 20, 2007


Discriminative Keyword Selection Using Support Vector Machines
Fred Richardson and William M. Campbell
Advances in Neural Information Processing Systems 20, 2007


Catching Change-points with Lasso
Céline Levy-leduc and Za\"ıd Harchaoui
Advances in Neural Information Processing Systems 20, 2007


Adaptive Online Gradient Descent
Elad Hazan, Alexander Rakhlin and Peter L. Bartlett
Advances in Neural Information Processing Systems 20, 2007


Computational Equivalence of Fixed Points and No Regret Algorithms, and Convergence to Equilibria
Elad Hazan and Satyen Kale
Advances in Neural Information Processing Systems 20, 2007


Iterative Non-linear Dimensionality Reduction with Manifold Sculpting
Michael Gashler, Dan Ventura and Tony Martinez
Advances in Neural Information Processing Systems 20, 2007


Regret Minimization in Games with Incomplete Information
Martin Zinkevich, Michael Johanson, Michael Bowling and Carmelo Piccione
Advances in Neural Information Processing Systems 20, 2007


Modeling Natural Sounds with Modulation Cascade Processes
Richard Turner and Maneesh Sahani
Advances in Neural Information Processing Systems 20, 2007


A learning framework for nearest neighbor search
Lawrence Cayton and Sanjoy Dasgupta
Advances in Neural Information Processing Systems 20, 2007


Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs
Ambuj Tewari and Peter L. Bartlett
Advances in Neural Information Processing Systems 20, 2007


Distributed Inference for Latent Dirichlet Allocation
David Newman, Padhraic Smyth, Max Welling and Arthur U. Asuncion
Advances in Neural Information Processing Systems 20, 2007


Variational inference for Markov jump processes
Manfred Opper and Guido Sanguinetti
Advances in Neural Information Processing Systems 20, 2007


Modelling motion primitives and their timing in biologically executed movements
Ben Williams, Marc Toussaint and Amos J. Storkey
Advances in Neural Information Processing Systems 20, 2007


The Noisy-Logical Distribution and its Application to Causal Inference
Hongjing Lu and Alan L. Yuille
Advances in Neural Information Processing Systems 20, 2007


Efficient Bayesian Inference for Dynamically Changing Graphs
Ozgur Sumer, Umut Acar, Alexander T. Ihler and Ramgopal R. Mettu
Advances in Neural Information Processing Systems 20, 2007


Configuration Estimates Improve Pedestrian Finding
Duan Tran and David A. Forsyth
Advances in Neural Information Processing Systems 20, 2007


Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity
Dejan Pecevski, Wolfgang Maass and Robert A. Legenstein
Advances in Neural Information Processing Systems 20, 2007


Mining Internet-Scale Software Repositories
Erik Linstead, Paul Rigor, Sushil Bajracharya, Cristina Lopes and Pierre F. Baldi
Advances in Neural Information Processing Systems 20, 2007


Online Linear Regression and Its Application to Model-Based Reinforcement Learning
Alexander L. Strehl and Michael L. Littman
Advances in Neural Information Processing Systems 20, 2007


Discriminative Log-Linear Grammars with Latent Variables
Slav Petrov and Dan Klein
Advances in Neural Information Processing Systems 20, 2007


Simulated Annealing: Rigorous finite-time guarantees for optimization on continuous domains
Andrea Lecchini-visintini, John Lygeros and Jan Maciejowski
Advances in Neural Information Processing Systems 20, 2007


Learning Bounds for Domain Adaptation
John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira and Jennifer Wortman
Advances in Neural Information Processing Systems 20, 2007


Efficient multiple hyperparameter learning for log-linear models
Chuan-sheng Foo, Chuong B. Do and Andrew Y. Ng
Advances in Neural Information Processing Systems 20, 2007


Hierarchical Penalization
Marie Szafranski, Yves Grandvalet and Pierre Morizet-mahoudeaux
Advances in Neural Information Processing Systems 20, 2007


COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking
Markus Weimer, Alexandros Karatzoglou, Quoc V. Le and Alex J. Smola
Advances in Neural Information Processing Systems 20, 2007


Extending position/phase-shift tuning to motion energy neurons improves velocity discrimination
Yiu M. Lam and Bertram E. Shi
Advances in Neural Information Processing Systems 20, 2007


Learning to classify complex patterns using a VLSI network of spiking neurons
Srinjoy Mitra, Giacomo Indiveri and Stefano Fusi
Advances in Neural Information Processing Systems 20, 2007


FilterBoost: Regression and Classification on Large Datasets
Joseph K. Bradley and Robert E. Schapire
Advances in Neural Information Processing Systems 20, 2007


Competition Adds Complexity
Judy Goldsmith and Martin Mundhenk
Advances in Neural Information Processing Systems 20, 2007


Agreement-Based Learning
Percy Liang, Dan Klein and Michael I. Jordan
Advances in Neural Information Processing Systems 20, 2007


Modeling homophily and stochastic equivalence in symmetric relational data
Peter Hoff
Advances in Neural Information Processing Systems 20, 2007


Exponential Family Predictive Representations of State
David Wingate and Satinder S. Baveja
Advances in Neural Information Processing Systems 20, 2007


A Risk Minimization Principle for a Class of Parzen Estimators
Kristiaan Pelckmans, Johan Suykens and Bart D. Moor
Advances in Neural Information Processing Systems 20, 2007


Stable Dual Dynamic Programming
Tao Wang, Michael Bowling, Dale Schuurmans and Daniel J. Lizotte
Advances in Neural Information Processing Systems 20, 2007


Convex Relaxations of Latent Variable Training
Yuhong Guo and Dale Schuurmans
Advances in Neural Information Processing Systems 20, 2007


Multiple-Instance Pruning For Learning Efficient Cascade Detectors
Cha Zhang and Paul A. Viola
Advances in Neural Information Processing Systems 20, 2007


Measuring Neural Synchrony by Message Passing
Justin Dauwels, François Vialatte, Tomasz Rutkowski and Andrzej S. Cichocki
Advances in Neural Information Processing Systems 20, 2007


One-Pass Boosting
Zafer Barutcuoglu, Phil Long and Rocco Servedio
Advances in Neural Information Processing Systems 20, 2007


Topmoumoute Online Natural Gradient Algorithm
Nicolas L. Roux, Pierre-antoine Manzagol and Yoshua Bengio
Advances in Neural Information Processing Systems 20, 2007


Kernel Measures of Conditional Dependence
Kenji Fukumizu, Arthur Gretton, Xiaohai Sun and Bernhard Schölkopf
Advances in Neural Information Processing Systems 20, 2007


Continuous Time Particle Filtering for fMRI
Lawrence Murray and Amos J. Storkey
Advances in Neural Information Processing Systems 20, 2007


The Generalized FITC Approximation
Andrew Naish-guzman and Sean Holden
Advances in Neural Information Processing Systems 20, 2007


Learning Visual Attributes
Vittorio Ferrari and Andrew Zisserman
Advances in Neural Information Processing Systems 20, 2007


Learning and using relational theories
Charles Kemp, Noah Goodman and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 20, 2007


Adaptive Embedded Subgraph Algorithms using Walk-Sum Analysis
Venkat Chandrasekaran, Alan S. Willsky and Jason K. Johnson
Advances in Neural Information Processing Systems 20, 2007


On Ranking in Survival Analysis: Bounds on the Concordance Index
Harald Steck, Balaji Krishnapuram, Cary Dehing-oberije, Philippe Lambin and Vikas C. Raykar
Advances in Neural Information Processing Systems 20, 2007


Efficient Convex Relaxation for Transductive Support Vector Machine
Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King and Michael Lyu
Advances in Neural Information Processing Systems 20, 2007


Collective Inference on Markov Models for Modeling Bird Migration
M.a. S. Elmohamed, Dexter Kozen and Daniel R. Sheldon
Advances in Neural Information Processing Systems 20, 2007


A Randomized Algorithm for Large Scale Support Vector Learning
Krishnan Kumar, Chiru Bhattacharya and Ramesh Hariharan
Advances in Neural Information Processing Systems 20, 2007


Temporal Difference Updating without a Learning Rate
Marcus Hutter and Shane Legg
Advances in Neural Information Processing Systems 20, 2007


Nearest-Neighbor-Based Active Learning for Rare Category Detection
Jingrui He and Jaime G. Carbonell
Advances in Neural Information Processing Systems 20, 2007


Support Vector Machine Classification with Indefinite Kernels
Ronny Luss and Alexandre D'aspremont
Advances in Neural Information Processing Systems 20, 2007


Bayesian Co-Training
Shipeng Yu, Balaji Krishnapuram, Harald Steck, R. B. Rao and Rómer Rosales
Advances in Neural Information Processing Systems 20, 2007


How SVMs can estimate quantiles and the median
Andreas Christmann and Ingo Steinwart
Advances in Neural Information Processing Systems 20, 2007


Colored Maximum Variance Unfolding
Le Song, Arthur Gretton, Karsten M. Borgwardt and Alex J. Smola
Advances in Neural Information Processing Systems 20, 2007


Progressive mixture rules are deviation suboptimal
Jean-yves Audibert
Advances in Neural Information Processing Systems 20, 2007


GRIFT: A graphical model for inferring visual classification features from human data
Michael Ross and Andrew Cohen
Advances in Neural Information Processing Systems 20, 2007


Bundle Methods for Machine Learning
Quoc V. Le, Alex J. Smola and S.v.n. Vishwanathan
Advances in Neural Information Processing Systems 20, 2007


A neural network implementing optimal state estimation based on dynamic spike train decoding
Omer Bobrowski, Ron Meir, Shy Shoham and Yonina Eldar
Advances in Neural Information Processing Systems 20, 2007


Multi-Task Learning via Conic Programming
Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama and Kiyoshi Asai
Advances in Neural Information Processing Systems 20, 2007


A probabilistic model for generating realistic lip movements from speech
Gwenn Englebienne, Tim Cootes and Magnus Rattray
Advances in Neural Information Processing Systems 20, 2007


Heterogeneous Component Analysis
Shigeyuki Oba, Motoaki Kawanabe, Klaus-robert Müller and Shin Ishii
Advances in Neural Information Processing Systems 20, 2007


A Unified Near-Optimal Estimator For Dimension Reduction in $l_\alpha$ ($0<\alpha\leq 2$) Using Stable Random Projections
Ping Li and Trevor J. Hastie
Advances in Neural Information Processing Systems 20, 2007


Parallelizing Support Vector Machines on Distributed Computers
Kaihua Zhu, Hao Wang, Hongjie Bai, Jian Li, Zhihuan Qiu, Hang Cui and Edward Y. Chang
Advances in Neural Information Processing Systems 20, 2007


Multi-task Gaussian Process Prediction
Edwin V. Bonilla, Kian M. Chai and Christopher Williams
Advances in Neural Information Processing Systems 20, 2007


Optimal ROC Curve for a Combination of Classifiers
Marco Barreno, Alvaro Cardenas and J. D. Tygar
Advances in Neural Information Processing Systems 20, 2007


Consistent Minimization of Clustering Objective Functions
Ulrike V. Luxburg, Stefanie Jegelka, Michael Kaufmann and Sébastien Bubeck
Advances in Neural Information Processing Systems 20, 2007


Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking Neurons
Lars Buesing and Wolfgang Maass
Advances in Neural Information Processing Systems 20, 2007


SpAM: Sparse Additive Models
Han Liu, Larry Wasserman, John D. Lafferty and Pradeep K. Ravikumar
Advances in Neural Information Processing Systems 20, 2007


Rapid Inference on a Novel AND/OR graph for Object Detection, Segmentation and Parsing
Yuanhao Chen, Long Zhu, Chenxi Lin, Hongjiang Zhang and Alan L. Yuille
Advances in Neural Information Processing Systems 20, 2007


Optimal models of sound localization by barn owls
Brian J. Fischer
Advances in Neural Information Processing Systems 20, 2007


Learning Horizontal Connections in a Sparse Coding Model of Natural Images
Pierre Garrigues and Bruno A. Olshausen
Advances in Neural Information Processing Systems 20, 2007


Comparing Bayesian models for multisensory cue combination without mandatory integration
Ulrik Beierholm, Ladan Shams, Wei J. Ma and Konrad Koerding
Advances in Neural Information Processing Systems 20, 2007


Inferring Neural Firing Rates from Spike Trains Using Gaussian Processes
John P. Cunningham, Byron M. Yu and Krishna V. Shenoy
Advances in Neural Information Processing Systems 20, 2007


Theoretical Analysis of Heuristic Search Methods for Online POMDPs
Stephane Ross, Joelle Pineau and Brahim Chaib-draa
Advances in Neural Information Processing Systems 20, 2007


Experience-Guided Search: A Theory of Attentional Control
David Baldwin and Michael C. Mozer
Advances in Neural Information Processing Systems 20, 2007


Scan Strategies for Meteorological Radars
Victoria Manfredi and Jim Kurose
Advances in Neural Information Processing Systems 20, 2007


Boosting the Area under the ROC Curve
Phil Long and Rocco Servedio
Advances in Neural Information Processing Systems 20, 2007


A Constraint Generation Approach to Learning Stable Linear Dynamical Systems
Byron Boots, Geoffrey J. Gordon and Sajid M. Siddiqi
Advances in Neural Information Processing Systems 20, 2007


Retrieved context and the discovery of semantic structure
Vinayak Rao and Marc Howard
Advances in Neural Information Processing Systems 20, 2007


Better than least squares: comparison of objective functions for estimating linear-nonlinear models
Tatyana Sharpee
Advances in Neural Information Processing Systems 20, 2007


The Infinite Gamma-Poisson Feature Model
Michalis K. Titsias
Advances in Neural Information Processing Systems 20, 2007


Random Sampling of States in Dynamic Programming
Chris Atkeson and Benjamin Stephens
Advances in Neural Information Processing Systems 20, 2007


Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations
M. M. Mahmud and Sylvian Ray
Advances in Neural Information Processing Systems 20, 2007


Convex Clustering with Exemplar-Based Models
Danial Lashkari and Polina Golland
Advances in Neural Information Processing Systems 20, 2007


Near-Maximum Entropy Models for Binary Neural Representations of Natural Images
Matthias Bethge and Philipp Berens
Advances in Neural Information Processing Systems 20, 2007


Incremental Natural Actor-Critic Algorithms
Shalabh Bhatnagar, Mohammad Ghavamzadeh, Mark Lee and Richard S. Sutton
Advances in Neural Information Processing Systems 20, 2007


Statistical Analysis of Semi-Supervised Regression
Larry Wasserman and John D. Lafferty
Advances in Neural Information Processing Systems 20, 2007


Markov Chain Monte Carlo with People
Adam Sanborn and Thomas L. Griffiths
Advances in Neural Information Processing Systems 20, 2007


Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Sebastian Gerwinn, Matthias Bethge, Jakob H. Macke and Matthias Seeger
Advances in Neural Information Processing Systems 20, 2007


Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression
Sennay Ghebreab, Arnold Smeulders and Pieter Adriaans
Advances in Neural Information Processing Systems 20, 2007


An Analysis of Convex Relaxations for MAP Estimation
Pawan Mudigonda, Vladimir Kolmogorov and Philip Torr
Advances in Neural Information Processing Systems 20, 2007


Contraction Properties of VLSI Cooperative Competitive Neural Networks of Spiking Neurons
Emre Neftci, Elisabetta Chicca, Giacomo Indiveri, Jean-jeacques Slotine and Rodney J. Douglas
Advances in Neural Information Processing Systems 20, 2007


What makes some POMDP problems easy to approximate?
Wee S. Lee, Nan Rong and Daniel J. Hsu
Advances in Neural Information Processing Systems 20, 2007


Scene Segmentation with CRFs Learned from Partially Labeled Images
Bill Triggs and Jakob J. Verbeek
Advances in Neural Information Processing Systems 20, 2007


On higher-order perceptron algorithms
Claudio Gentile, Fabio Vitale and Cristian Brotto
Advances in Neural Information Processing Systems 20, 2007


Receptive Fields without Spike-Triggering
Guenther Zeck, Matthias Bethge and Jakob H. Macke
Advances in Neural Information Processing Systems 20, 2007


Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashima, Paul V. Buenau and Motoaki Kawanabe
Advances in Neural Information Processing Systems 20, 2007


Classification via Minimum Incremental Coding Length (MICL)
John Wright, Yangyu Tao, Zhouchen Lin, Yi Ma and Heung-yeung Shum
Advances in Neural Information Processing Systems 20, 2007


Anytime Induction of Cost-sensitive Trees
Saher Esmeir and Shaul Markovitch
Advances in Neural Information Processing Systems 20, 2007


Learning with Transformation Invariant Kernels
Christian Walder and Olivier Chapelle
Advances in Neural Information Processing Systems 20, 2007


Selecting Observations against Adversarial Objectives
Andreas Krause, Brendan Mcmahan, Carlos Guestrin and Anupam Gupta
Advances in Neural Information Processing Systems 20, 2007


Stability Bounds for Non-i.i.d. Processes
Mehryar Mohri and Afshin Rostamizadeh
Advances in Neural Information Processing Systems 20, 2007


Compressed Regression
Shuheng Zhou, Larry Wasserman and John D. Lafferty
Advances in Neural Information Processing Systems 20, 2007


HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation
Bing Zhao and Eric P. Xing
Advances in Neural Information Processing Systems 20, 2007


A Spectral Regularization Framework for Multi-Task Structure Learning
Andreas Argyriou, Massimiliano Pontil, Yiming Ying and Charles A. Micchelli
Advances in Neural Information Processing Systems 20, 2007


A general agnostic active learning algorithm
Sanjoy Dasgupta, Claire Monteleoni and Daniel J. Hsu
Advances in Neural Information Processing Systems 20, 2007


An online Hebbian learning rule that performs Independent Component Analysis
Claudia Clopath, André Longtin and Wulfram Gerstner
Advances in Neural Information Processing Systems 20, 2007


Inferring Elapsed Time from Stochastic Neural Processes
Misha Ahrens and Maneesh Sahani
Advances in Neural Information Processing Systems 20, 2007


Regularized Boost for Semi-Supervised Learning
Ke Chen and Shihai Wang
Advances in Neural Information Processing Systems 20, 2007


Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms
Dominik Endres, Mike Oram, Johannes Schindelin and Peter Foldiak
Advances in Neural Information Processing Systems 20, 2007


Ensemble Clustering using Semidefinite Programming
Vikas Singh, Lopamudra Mukherjee, Jiming Peng and Jinhui Xu
Advances in Neural Information Processing Systems 20, 2007


Learning the structure of manifolds using random projections
Yoav Freund, Sanjoy Dasgupta, Mayank Kabra and Nakul Verma
Advances in Neural Information Processing Systems 20, 2007


Kernels on Attributed Pointsets with Applications
Mehul Parsana, Sourangshu Bhattacharya, Chiru Bhattacharya and K. Ramakrishnan
Advances in Neural Information Processing Systems 20, 2007


Bayesian Policy Learning with Trans-Dimensional MCMC
Matthew Hoffman, Arnaud Doucet, Nando D. Freitas and Ajay Jasra
Advances in Neural Information Processing Systems 20, 2007


Discovering Weakly-Interacting Factors in a Complex Stochastic Process
Charlie Frogner and Avi Pfeffer
Advances in Neural Information Processing Systems 20, 2007


Sparse Feature Learning for Deep Belief Networks
Marc'aurelio Ranzato, Y-lan Boureau and Yann L. Cun
Advances in Neural Information Processing Systems 20, 2007


An in-silico Neural Model of Dynamic Routing through Neuronal Coherence
Devarajan Sridharan, Brian Percival, John Arthur and Kwabena A. Boahen
Advances in Neural Information Processing Systems 20, 2007


Receding Horizon Differential Dynamic Programming
Yuval Tassa, Tom Erez and William D. Smart
Advances in Neural Information Processing Systems 20, 2007


Random Projections for Manifold Learning
Chinmay Hegde, Michael Wakin and Richard Baraniuk
Advances in Neural Information Processing Systems 20, 2007


People Tracking with the Laplacian Eigenmaps Latent Variable Model
Zhengdong Lu, Cristian Sminchisescu and Miguel Á. Carreira-perpiñán
Advances in Neural Information Processing Systems 20, 2007


Variational Inference for Diffusion Processes
Cédric Archambeau, Manfred Opper, Yuan Shen, Dan Cornford and John S. Shawe-taylor
Advances in Neural Information Processing Systems 20, 2007


Learning with Tree-Averaged Densities and Distributions
Sergey Kirshner
Advances in Neural Information Processing Systems 20, 2007


Loop Series and Bethe Variational Bounds in Attractive Graphical Models
Alan S. Willsky, Erik B. Sudderth and Martin J. Wainwright
Advances in Neural Information Processing Systems 20, 2007


Estimating disparity with confidence from energy neurons
Eric K. Tsang and Bertram E. Shi
Advances in Neural Information Processing Systems 20, 2007


Predicting human gaze using low-level saliency combined with face detection
Moran Cerf, Jonathan Harel, Wolfgang Einhaeuser and Christof Koch
Advances in Neural Information Processing Systems 20, 2007


Multiple-Instance Active Learning
Burr Settles, Mark Craven and Soumya Ray
Advances in Neural Information Processing Systems 20, 2007


Ultrafast Monte Carlo for Statistical Summations
Charles L. Isbell, Michael P. Holmes and Alexander G. Gray
Advances in Neural Information Processing Systems 20, 2007


Density Estimation under Independent Similarly Distributed Sampling Assumptions
Tony Jebara, Yingbo Song and Kapil Thadani
Advances in Neural Information Processing Systems 20, 2007


Testing for Homogeneity with Kernel Fisher Discriminant Analysis
Moulines Eric, Francis R. Bach and Za\"ıd Harchaoui
Advances in Neural Information Processing Systems 20, 2007


Feature Selection Methods for Improving Protein Structure Prediction with Rosetta
Ben Blum, Rhiju Das, Philip Bradley, David Baker, Michael I. Jordan and David Tax
Advances in Neural Information Processing Systems 20, 2007


On Sparsity and Overcompleteness in Image Models
Pietro Berkes, Richard Turner and Maneesh Sahani
Advances in Neural Information Processing Systems 20, 2007


Convex Learning with Invariances
Choon H. Teo, Amir Globerson, Sam T. Roweis and Alex J. Smola
Advances in Neural Information Processing Systems 20, 2007


Learning Monotonic Transformations for Classification
Andrew Howard and Tony Jebara
Advances in Neural Information Processing Systems 20, 2007


Sparse Overcomplete Latent Variable Decomposition of Counts Data
Madhusudana Shashanka, Bhiksha Raj and Paris Smaragdis
Advances in Neural Information Processing Systems 20, 2007


Semi-Supervised Multitask Learning
Qiuhua Liu, Xuejun Liao and Lawrence Carin
Advances in Neural Information Processing Systems 20, 2007


EEG-Based Brain-Computer Interaction: Improved Accuracy by Automatic Single-Trial Error Detection
Pierre Ferrez and José Millán
Advances in Neural Information Processing Systems 20, 2007


Efficient Principled Learning of Thin Junction Trees
Anton Chechetka and Carlos Guestrin
Advances in Neural Information Processing Systems 20, 2007


Spatial Latent Dirichlet Allocation
Xiaogang Wang and Eric Grimson
Advances in Neural Information Processing Systems 20, 2007


A Bayesian Model of Conditioned Perception
Alan Stocker and Eero P. Simoncelli
Advances in Neural Information Processing Systems 20, 2007


Probabilistic Matrix Factorization
Andriy Mnih and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 20, 2007


The Value of Labeled and Unlabeled Examples when the Model is Imperfect
Kaushik Sinha and Mikhail Belkin
Advances in Neural Information Processing Systems 20, 2007


The rat as particle filter
Aaron C. Courville and Nathaniel D. Daw
Advances in Neural Information Processing Systems 20, 2007


Infinite State Bayes-Nets for Structured Domains
Max Welling, Ian Porteous and Evgeniy Bart
Advances in Neural Information Processing Systems 20, 2007


Loop Corrections for Approximate Inference on Factor Graphs
Joris M. Mooij and Hilbert J. Kappen
Journal of Machine Learning Research, 2007


Multi-class Protein Classification Using Adaptive Codes
Iain Melvin, Eugene Ie, Jason Weston, William S. Noble and Christina S. Leslie
Journal of Machine Learning Research, 2007


Concave Learners for Rankboost
Ofer Melnik, Yehuda Vardi and Cun-hui Zhang
Journal of Machine Learning Research, 2007


Boosted Classification Trees and Class Probability/Quantile Estimation
David Mease, Abraham J. Wyner and Andreas Buja
Journal of Machine Learning Research, 2007


Proto-value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes
Sridhar Mahadevan and Mauro Maggioni
Journal of Machine Learning Research, 2007


Classification in Networked Data: A Toolkit and a Univariate Case Study
Sofus A. Macskassy and Foster J. Provost
Journal of Machine Learning Research, 2007


Comments on the "Core Vector Machines: Fast SVM Training on Very Large Data Sets"
Ga\"elle Loosli and Stéphane Canu
Journal of Machine Learning Research, 2007


A Complete Characterization of a Family of Solutions to a Generalized Fisher Criterion
Marco Loog
Journal of Machine Learning Research, 2007


Local Discriminant Wavelet Packet Coordinates for Face Recognition
Chao-chun Liu, Dao-qing Dai and Hong Yan
Journal of Machine Learning Research, 2007


General Polynomial Time Decomposition Algorithms
Nikolas List and Hans-ulrich Simon
Journal of Machine Learning Research, 2007


A Nonparametric Statistical Approach to Clustering via Mode Identification
Jia Li, Surajit Ray and Bruce G. Lindsay
Journal of Machine Learning Research, 2007


Nonlinear Estimators and Tail Bounds for Dimension Reduction in {\it l}$_{\mbox{1}}$ Using Cauchy Random Projections
Ping Li, Trevor Hastie and Kenneth W. Church
Journal of Machine Learning Research, 2007


The Locally Weighted Bag of Words Framework for Document Representation
Guy Lebanon, Yi Mao and Joshua V. Dillon
Journal of Machine Learning Research, 2007


PAC-Bayes Risk Bounds for Stochastic Averages and Majority Votes of Sample-Compressed Classifiers
Françcois Laviolette and Mario Marchand
Journal of Machine Learning Research, 2007


Integrating Na\"{\i}ve Bayes and FOIL
Niels Landwehr, Kristian Kersting and Luc D. Raedt
Journal of Machine Learning Research, 2007


Unlabeled Compression Schemes for Maximum Classes
Dima Kuzmin and Manfred K. Warmuth
Journal of Machine Learning Research, 2007


Measuring Differentiability: Unmasking Pseudonymous Authors
Moshe Koppel, Jonathan Schler and Elisheva Bonchek-dokow
Journal of Machine Learning Research, 2007


Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts
J. Z. Kolter and Marcus A. Maloof
Journal of Machine Learning Research, 2007


An Interior-Point Method for Large-Scale {\it l}$_{\mbox{1}}$-Regularized Logistic Regression
Kwangmoo Koh, Seung-jean Kim and Stephen P. Boyd
Journal of Machine Learning Research, 2007


Noise Tolerant Variants of the Perceptron Algorithm
Roni Khardon and Gabriel Wachman
Journal of Machine Learning Research, 2007


Estimating High-Dimensional Directed Acyclic Graphs with the PC-Algorithm
Markus Kalisch and Peter Bühlmann
Journal of Machine Learning Research, 2007


On the Effectiveness of Laplacian Normalization for Graph Semi-supervised Learning
Rie Johnson and Tong Zhang
Journal of Machine Learning Research, 2007


Revised Loss Bounds for the Set Covering Machine and Sample-Compression Loss Bounds for Imbalanced Data
Zakria Hussain, Françcois Laviolette, Mario Marchand, John Shawe-taylor, S. C. Brubaker and Matthew D. Mullin
Journal of Machine Learning Research, 2007


A New Probabilistic Approach in Rank Regression with Optimal Bayesian Partitioning
Carine Hue and Marc Boullé
Journal of Machine Learning Research, 2007


Structure and Majority Classes in Decision Tree Learning
Ray J. Hickey
Journal of Machine Learning Research, 2007


Graph Laplacians and their Convergence on Random Neighborhood Graphs
Matthias Hein, Jean-yves Audibert and Ulrike V. Luxburg
Journal of Machine Learning Research, 2007


Spherical-Homoscedastic Distributions: The Equivalency of Spherical and Normal Distributions in Classification
Onur C. Hamsici and Aleix M. Mart\'ınez
Journal of Machine Learning Research, 2007


The On-Line Shortest Path Problem Under Partial Monitoring
András György, Tamás Linder, Gábor Lugosi and György Ottucsák
Journal of Machine Learning Research, 2007


Fast Iterative Kernel Principal Component Analysis
Simon Günter, Nicol N. Schraudolph and S. Vishwanathan
Journal of Machine Learning Research, 2007


VC Theory of Large Margin Multi-Category Classifiers
Yann Guermeur
Journal of Machine Learning Research, 2007


The Pyramid Match Kernel: Efficient Learning with Sets of Features
Kristen Grauman and Trevor Darrell
Journal of Machine Learning Research, 2007


Truncating the Loop Series Expansion for Belief Propagation
Vicençc Gómez, Joris M. Mooij and Hilbert J. Kappen
Journal of Machine Learning Research, 2007


Euclidean Embedding of Co-occurrence Data
Amir Globerson, Gal Chechik, Fernando Pereira and Naftali Tishby
Journal of Machine Learning Research, 2007


Hierarchical Average Reward Reinforcement Learning
Mohammad Ghavamzadeh and Sridhar Mahadevan
Journal of Machine Learning Research, 2007


Nonlinear Boosting Projections for Ensemble Construction
Nicolás Garc\'ıa-pedrajas, Cesar Garc\'ıa-osorio and Colin Fyfe
Journal of Machine Learning Research, 2007


A Stochastic Algorithm for Feature Selection in Pattern Recognition
Sébastien Gadat and Laurent Younes
Journal of Machine Learning Research, 2007


Harnessing the Expertise of 70, 000 Human Editors: Knowledge-Based Feature Generation for Text Categorization
Evgeniy Gabrilovich and Shaul Markovitch
Journal of Machine Learning Research, 2007


Statistical Consistency of Kernel Canonical Correlation Analysis
Kenji Fukumizu, Francis R. Bach and Arthur Gretton
Journal of Machine Learning Research, 2007


Attribute-Efficient and Non-adaptive Learning of Parities and DNF Expressions
Vitaly Feldman
Journal of Machine Learning Research, 2007


Anytime Learning of Decision Trees
Saher Esmeir and Shaul Markovitch
Journal of Machine Learning Research, 2007


"Ideal Parent" Structure Learning for Continuous Variable Bayesian Networks
Gal Elidan, Iftach Nachman and Nir Friedman
Journal of Machine Learning Research, 2007


Separating Models of Learning from Correlated and Uncorrelated Data
Ariel Elbaz, Homin K. Lee, Rocco A. Servedio and Andrew Wan
Journal of Machine Learning Research, 2007


Bilinear Discriminant Component Analysis
Mads Dyrholm, Christoforos Christoforou and Lucas C. Parra
Journal of Machine Learning Research, 2007


Maximum Entropy Density Estimation with Generalized Regularization and an Application to Species Distribution Modeling
Miroslav Dudík, Steven J. Phillips and Robert E. Schapire
Journal of Machine Learning Research, 2007


On the Representer Theorem and Equivalent Degrees of Freedom of SVR
Francesco Dinuzzo, Marta Neve, Giuseppe D. Nicolao and Ugo P. Gianazza
Journal of Machine Learning Research, 2007


Online Learning of Multiple Tasks with a Shared Loss
Ofer Dekel, Philip M. Long and Yoram Singer
Journal of Machine Learning Research, 2007


A Probabilistic Analysis of EM for Mixtures of Separated, Spherical Gaussians
Sanjoy Dasgupta and Leonard J. Schulman
Journal of Machine Learning Research, 2007


Ranking the Best Instances
Stéphan Clémençcon and Nicolas Vayatis
Journal of Machine Learning Research, 2007


Polynomial Identification in the Limit of Substitutable Context-free Languages
Alexander Clark and Rémi Eyraud
Journal of Machine Learning Research, 2007


Behavioral Shaping for Geometric Concepts
Manu Chhabra, Robert A. Jacobs and Daniel Stefankovic
Journal of Machine Learning Research, 2007


Very Fast Online Learning of Highly Non Linear Problems
Aggelos Chariatis
Journal of Machine Learning Research, 2007


{\it Gini} Support Vector Machine: Quadratic Entropy Based Robust Multi-Class Probability Regression
Shantanu Chakrabartty and Gert Cauwenberghs
Journal of Machine Learning Research, 2007


Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters
Gavin C. Cawley and Nicola Talbot
Journal of Machine Learning Research, 2007


Learning to Classify Ordinal Data: The Data Replication Method
Jaime S. Cardoso and Joaquim Costa
Journal of Machine Learning Research, 2007


Compression-Based Averaging of Selective Naive Bayes Classifiers
Marc Boullé
Journal of Machine Learning Research, 2007


From External to Internal Regret
Avrim Blum and Yishay Mansour
Journal of Machine Learning Research, 2007


Dynamics and Generalization Ability of LVQ Algorithms
Michael Biehl, Anarta Ghosh and Barbara Hammer
Journal of Machine Learning Research, 2007


AdaBoost is Consistent
Peter L. Bartlett and Mikhail Traskin
Journal of Machine Learning Research, 2007


Sparseness vs Estimating Conditional Probabilities: Some Asymptotic Results
Peter L. Bartlett and Ambuj Tewari
Journal of Machine Learning Research, 2007


A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu and Dharmendra S. Modha
Journal of Machine Learning Research, 2007


Combining PAC-Bayesian and Generic Chaining Bounds
Jean-yves Audibert and Olivier Bousquet
Journal of Machine Learning Research, 2007


Learning Horn Expressions with LOGAN-H
Marta Arias, Roni Khardon and Jérôme Maloberti
Journal of Machine Learning Research, 2007


Minimax Regret Classifier for Imprecise Class Distributions
Roc\'ıo Ala\'ız-rodr\'ıguez, Alicia Guerrero-curieses and Jes\'us Cid-sueiro
Journal of Machine Learning Research, 2007


Generalized Do-Calculus with Testable Causal Assumptions
Jiji Zhang
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Importance Sampling for General Hybrid Bayesian Networks
Changhe Yuan and Marek J. Druzdzel
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Nonnegative Garrote Component Selection in Functional ANOVA models
Ming Yuan
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


SVM versus Least Squares SVM
Jieping Ye and Tao Xiong
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


How Powerful Can Any Regression Learning Procedure Be?
Yuhong Yang
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Transductive Classification via Local Learning Regularization
Mingrui Wu and Bernhard Schölkopf
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Performance Guarantees for Information Theoretic Active Inference
Jason L. Williams, John Iii and Alan S. Willsky
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Metric Learning for Kernel Regression
Kilian Q. Weinberger and Gerald Tesauro
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


The Kernel Path in Kernelized LASSO
Gang Wang, Dit-yan Yeung and Frederick H. Lochovsky
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Semi-Supervised Mean Fields
Fei Wang, Shijun Wang, Changshui Zhang and Ole Winther
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Fast Mean Shift with Accurate and Stable Convergence
Ping Wang, Dongryeol Lee, Alexander G. Gray and James M. Rehg
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Efficient large margin semisupervised learning
Junhui Wang
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Nonlinear Dimensionality Reduction as Information Retrieval
Jarkko Venna and Samuel Kaski
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Hierarchical Beta Processes and the Indian Buffet Process
Romain Thibaux and Michael I. Jordan
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Stick-breaking Construction for the Indian Buffet Process
Yee W. Teh, Dilan Görür and Zoubin Ghahramani
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Learning Multilevel Distributed Representations for High-Dimensional Sequences
Ilya Sutskever and Geoffrey E. Hinton
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Emerge and spread models and word burstiness
Peter Sunehag
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Predictive Discretization during Model Selection
Harald Steck and Tommi Jaakkola
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Local and global sparse Gaussian process approximations
Edward Snelson and Zoubin Ghahramani
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Generalized Darting Monte Carlo
Cristian Sminchisescu and Max Welling
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Dynamic Factorization Tests: Applications to Multi-modal Data Association
Michael Siracusa and John Iii
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Analogical Reasoning with Relational Bayesian Sets
Ricardo Silva, Katherine A. Heller and Zoubin Ghahramani
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Fast State Discovery for HMM Model Selection and Learning
Sajid M. Siddiqi, Geoffrey J. Gordon and Andrew W. Moore
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Ellipsoidal Machines
Pannagadatta K. Shivaswamy and Tony Jebara
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Fast Kernel ICA using an Approximate Newton Method
Hao Shen, Stefanie Jegelka and Arthur Gretton
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Framework for Probability Density Estimation
John Shawe-taylor and Alexander N. Dolia
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Minimum Volume Embedding
Blake Shaw and Tony Jebara
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Unified Algorithmic Approach for Efficient Online Label Ranking
Shai Shalev-shwartz and Yoram Singer
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Bayesian Inference and Optimal Design in the Sparse Linear Model
Matthias Seeger, Florian Steinke and Koji Tsuda
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Stochastic Quasi-Newton Method for Online Convex Optimization
Nicol N. Schraudolph, Jin Yu and Simon Günter
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Memory-Effcient Orthogonal Least Squares Kernel Density Estimation using Enhanced Empirical Cumulative Distribution Functions
Martin Schafföner, Edin Andelic, Marcel Katz, Sven E. Krüger and Andreas Wendemuth
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Latent Space Approach to Dynamic Embedding of Co-occurrence Data
Purnamrita Sarkar, Sajid M. Siddiqi and Geoffrey J. Gordon
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure
Ruslan Salakhutdinov and Geoffrey E. Hinton
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Continuous Neural Networks
Nicolas L. Roux and Yoshua Bengio
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


The Rademacher Complexity of Co-Regularized Kernel Classes
David S. Rosenberg and Peter L. Bartlett
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A fast algorithm for learning large scale preference relations
Vikas C. Raykar, Ramani Duraiswami and Balaji Krishnapuram
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


(Approximate) Subgradient Methods for Structured Prediction
Nathan D. Ratliff, J. A. Bagnell and Martin Zinkevich
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Unified Energy-Based Framework for Unsupervised Learning
Marc'aurelio Ranzato, Y-lan Boureau, Sumit Chopra and Yann Lecun
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Approximate Counting of Graphical Models Via MCMC
Jose M. Peña
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Margin based Transductive Graph Cuts using Linear Programming
Kristiaan Pelckmans, John Shawe-taylor, Johan Suykens and Bart D. Moor
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Maximum Entropy Correlated Equilibria
Luis E. Ortiz, Robert E. Schapire and Sham M. Kakade
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Inductive Transfer for Bayesian Network Structure Learning
Alexandru Niculescu-mizil and Rich Caruana
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Loop Corrected Belief Propagation
Joris M. Mooij, Bastian Wemmenhove, Bert Kappen and Tommaso Rizzo
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Fast Bundle-based Anytime Algorithm for Poker and other Convex Games
H. B. Mcmahan and Geoffrey J. Gordon
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


AClass: A simple, online, parallelizable algorithm for probabilistic classification
Vikash K. Mansinghka, Daniel M. Roy, Ryan Rifkin and Joshua B. Tenenbaum
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Recall Systems: Effcient Learning and Use of Category Indices
Omid Madani, Wiley Greiner, David Kempe and Mohammad R. Salavatipour
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Semi-supervised Clustering with Pairwise Constraints: A Discriminative Approach
Zhengdong Lu
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo
Han Liu, John D. Lafferty and Larry A. Wasserman
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Fisher Consistency of Multicategory Support Vector Machines
Yufeng Liu
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Bayesian Divergence Prior for Classiffier Adaptation
Xiao Li and Jeff Bilmes
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Efficient active learning with generalized linear models
Jeremy Lewi, Robert J. Butera and Liam Paninski
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Treelets | A Tool for Dimensionality Reduction and Multi-Scale Analysis of Unstructured Data
Ann B. Lee and Boaz Nadler
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Learning Nearest-Neighbor Quantizers from Labeled Data by Information Loss Minimization
Svetlana Lazebnik and Maxim Raginsky
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Learning for Larger Datasets with the Gaussian Process Latent Variable Model
Neil D. Lawrence
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Fast Low-Rank Semidefinite Programming for Embedding and Clustering
Brian Kulis, Arun C. Surendran and John C. Platt
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Incorporating Prior Knowledge on Features into Learning
Eyal Krupka and Naftali Tishby
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


MDL Histogram Density Estimation
Petri Kontkanen and Petri Myllymäki
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Multi-object tracking with representations of the symmetric group
Risi Kondor, Andrew Howard and Tony Jebara
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Learning Markov Structure by Maximum Entropy Relaxation
Jason K. Johnson, Venkat Chandrasekaran and Alan S. Willsky
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Loopy Belief Propagation for Bipartite Maximum Weight b-Matching
Bert C. Huang and Tony Jebara
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Nonparametric Bayesian Approach to Modeling Overlapping Clusters
Katherine A. Heller and Zoubin Ghahramani
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Information Retrieval by Inferring Implicit Queries from Eye Movements
David R. Hardoon, John Shawe-taylor, Antti Ajanki, Kai Puolamäki and Samuel Kaski
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Space-Efficient Sampling
Sudipto Guha and Andrew Mcgregor
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Hidden Topic Markov Models
Amit Gruber, Yair Weiss and Michal Rosen-zvi
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Dissimilarity in Graph-Based Semi-Supervised Classification
Andrew B. Goldberg, Xiaojin Zhu and Stephen J. Wright
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


SampleSearch: A Scheme that Searches for Consistent Samples
Vibhav Gogate and Rina Dechter
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Visualizing pairwise similarity via semidefinite programming
Amir Globerson and Sam T. Roweis
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Approximate inference using conditional entropy decompositions
Amir Globerson and Tommi Jaakkola
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Deterministic Annealing for Multiple-Instance Learning
Peter V. Gehler and Olivier Chapelle
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Online Learning of Search Heuristics
Michael Fink
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Exact Bayesian structure learning from uncertain interventions
Daniel Eaton and Kevin P. Murphy
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Learning A* underestimates: Using inference to guide inference
Gregory Druck, Mukund Narasimhan and Paul A. Viola
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Large-Margin Classification in Banach Spaces
Ricky Der and Daniel Lee
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Fast search for Dirichlet process mixture models
Hal Daume
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Solving Markov Random Fields with Spectral Relaxation
Timothée Cour and Jianbo Shi
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Visualizing Similarity Data with a Mixture of Maps
James Cook, Ilya Sutskever, Andriy Mnih and Geoffrey E. Hinton
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


The Laplacian Eigenmaps Latent Variable Model
Miguel Á. Carreira-perpiñán and Zhengdong Lu
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Hybrid Pareto Model for Conditional Density Estimation of Asymmetric Fat-Tail Data
Julie Carreau and Yoshua Bengio
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Kernel Multi-task Learning using Task-specific Features
Edwin V. Bonilla, Felix V. Agakov and Christopher Williams
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Mixture of Watson Distributions: A Generative Model for Hyperspherical Embeddings
Avleen S. Bijral, Markus Breitenbach and Gregory Z. Grudic
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Boosting Algorithm for Label Covering in Multilabel Problems
Yonatan Amit, Ofer Dekel and Yoram Singer
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Seeking The Truly Correlated Topic Posterior - on tight approximate inference of logistic-normal admixture model
Amr Ahmed and Eric P. Xing
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Generalized Non-metric Multidimensional Scaling
Sameer Agarwal, Josh Wills, Lawrence Cayton, Gert Lanckriet, David J. Kriegman and Serge Belongie
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Policy-Gradients for PSRs and POMDPs
Douglas Aberdeen, Olivier Buffet and Owen Thomas
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007