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All publications at Proceedings of the 24th International Conference on Machine Learning (ICML-07)
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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

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
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
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
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
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007

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

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

A recursive method for discriminative mixture learning
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
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
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

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