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All publications in 2006
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Learning user preferences for sets of objects
Marie Desjardins, Eric Eaton and Kiri Wagstaff
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Efficient lazy elimination for averaged one-dependence estimators
Fei Zheng and Geoffrey I. Webb
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Statistical debugging: simultaneous identification of multiple bugs
Alice X. Zheng, Michael I. Jordan, Ben Liblit, Mayur Naik and Alex Aiken
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Block-quantized kernel matrix for fast spectral embedding
Kai Zhang and James T. Kwok
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Collaborative ordinal regression
Shipeng Yu, Kai Yu, Volker Tresp and Hans-peter Kriegel
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Active learning via transductive experimental design
Kai Yu, Jinbo Bi and Volker Tresp
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Null space versus orthogonal linear discriminant analysis
Jieping Ye and Tao Xiong
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Semi-supervised nonlinear dimensionality reduction
Xin Yang, Haoying Fu, Hongyuan Zha and Jesse L. Barlow
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Discriminative unsupervised learning of structured predictors
Linli Xu, Dana F. Wilkinson, Finnegan Southey and Dale Schuurmans
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Bayesian multi-population haplotype inference via a hierarchical dirichlet process mixture
Eric P. Xing, Kyung-ah Sohn, Michael I. Jordan and Yee W. Teh
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

A duality view of spectral methods for dimensionality reduction
Lin Xiao, Jun Sun and Stephen P. Boyd
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Fast time series classification using numerosity reduction
Xiaopeng Xi, Eamonn J. Keogh, Christian R. Shelton, Li Wei and Chotirat A. Ratanamahatana
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Predictive state representations with options
Britton Wolfe and Satinder P. Singh
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
David Wingate and Satinder P. Singh
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Inference with the Universum
Jason Weston, Ronan Collobert, Fabian H. Sinz, Léon Bottou and Vladimir Vapnik
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Totally corrective boosting algorithms that maximize the margin
Manfred K. Warmuth, Jun Liao and Gunnar Rätsch
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Label propagation through linear neighborhoods
Fei Wang and Changshui Zhang
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Two-dimensional solution path for support vector regression
Gang Wang, Dit-yan Yeung and Frederick H. Lochovsky
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Topic modeling: beyond bag-of-words
Hanna M. Wallach
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Accelerated training of conditional random fields with stochastic gradient methods
Nicol N. Schraudolph, Mark W. Schmidt, Kevin P. Murphy and S.v.n. Vishwanathan
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Active sampling for detecting irrelevant features
Sriharsha Veeramachaneni, Emanuele Olivetti and Paolo Avesani
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Clustering graphs by weighted substructure mining
Koji Tsuda and Taku Kudo
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Probabilistic inference for solving discrete and continuous state Markov Decision Processes
Marc Toussaint and Amos J. Storkey
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Discriminative cluster analysis
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Bayesian regression with input noise for high dimensional data
Jo-anne Ting, Aaron D'souza and Stefan Schaal
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Fast and space efficient string kernels using suffix arrays
Choon H. Teo and S.v.n. Vishwanathan
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Multiclass reduced-set support vector machines
Benyang Tang and Dominic Mazzoni
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Iterative RELIEF for feature weighting
Yijun Sun and Jian Li
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Local Fisher discriminant analysis for supervised dimensionality reduction
Masashi Sugiyama
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Full Bayesian network classifiers
Jiang Su and Harry Zhang
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Experience-efficient learning in associative bandit problems
Alexander L. Strehl, Chris Mesterharm, Michael L. Littman and Haym Hirsh
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

PAC model-free reinforcement learning
Alexander L. Strehl, Lihong Li, Eric Wiewiora, John Langford and Michael L. Littman
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Bayesian pattern ranking for move prediction in the game of Go
David H. Stern, Ralf Herbrich and Thore Graepel
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

An investigation of computational and informational limits in Gaussian mixture clustering
Nathan Srebro, Gregory Shakhnarovich and Sam T. Roweis
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Classifying EEG for brain-computer interfaces: learning optimal filters for dynamical system features
Le Song and Julien Epps
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Feature subset selection bias for classification learning
Surendra K. Singhi and Huan Liu
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Deterministic annealing for semi-supervised kernel machines
Vikas Sindhwani, S. S. Keerthi and Olivier Chapelle
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

An intrinsic reward mechanism for efficient exploration
Özgür Simsek and Andrew G. Barto
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Bayesian learning of measurement and structural models
Ricardo Silva and Richard Scheines
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Dealing with non-stationary environments using context detection
Bruno Silva, Eduardo W. Basso, Ana Bazzan and Paulo M. Engel
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Permutation invariant SVMs
Pannagadatta K. Shivaswamy and Tony Jebara
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Feature value acquisition in testing: a sequential batch test algorithm
Victor S. Sheng and Charles X. Ling
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Cost-sensitive learning with conditional Markov networks
Prithviraj Sen and Lise Getoor
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Efficient inference on sequence segmentation models
Sunita Sarawagi
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Predictive linear-Gaussian models of controlled stochastic dynamical systems
Matthew R. Rudary and Satinder P. Singh
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

A statistical approach to rule learning
Ulrich Rückert and Stefan Kramer
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Josep Roure and Andrew W. Moore
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Combining discriminative features to infer complex trajectories
David A. Ross, Simon Osindero and Richard S. Zemel
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

How boosting the margin can also boost classifier complexity
Lev Reyzin and Robert E. Schapire
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Categorization in multiple category systems
Jean-michel Renders, Éric Gaussier, Cyril Goutte, Françcois Pacull and Gabriela Csurka
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Quadratic programming relaxations for metric labeling and Markov random field MAP estimation
Pradeep D. Ravikumar and John D. Lafferty
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Maximum margin planning
Nathan D. Ratliff, J. A. Bagnell and Martin Zinkevich
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

CN = CPCN
Liva Ralaivola, Françcois Denis and Christophe N. Magnan
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Constructing informative priors using transfer learning
Rajat Raina, Andrew Y. Ng and Daphne Koller
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

MISSL: multiple-instance semi-supervised learning
Rouhollah Rahmani and Sally A. Goldman
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

An analytic solution to discrete Bayesian reinforcement learning
Pascal Poupart, Nikos A. Vlassis, Jesse Hoey and Kevin Regan
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

The support vector decomposition machine
Francisco Pereira and Geoffrey J. Gordon
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Concept boundary detection for speeding up SVMs
Navneet Panda, Edward Y. Chang and Gang Wu
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Reinforcement learning for optimized trade execution
Yuriy Nevmyvaka, Yi Feng and Michael Kearns
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Learning hierarchical task networks by observation
Negin Nejati, Pat Langley and Tolga Könik
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Online decoding of Markov models under latency constraints
Mukund Narasimhan, Paul A. Viola and Michael Shilman
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Learning to impersonate
Moni Naor and Guy N. Rothblum
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Generalized spectral bounds for sparse LDA
Baback Moghaddam, Yair Weiss and Shai Avidan
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Kernel information embeddings
Roland Memisevic
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

The uniqueness of a good optimum for K-means
Marina Meila
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Learning high-order MRF priors of color images
Julian J. Mcauley, Tibério S. Caetano, Alex J. Smola and Matthias O. Franz
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Pruning in ordered bagging ensembles
Gonzalo Mart\'ınez-muñoz and Alberto Suárez
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Fast direct policy evaluation using multiscale analysis of Markov diffusion processes
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Combined central and subspace clustering for computer vision applications
Le Lu and René Vidal
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Spectral clustering for multi-type relational data
Bo Long, Zhongfei (. Zhang, Xiaoyun Wu and Philip S. Yu
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Pachinko allocation: DAG-structured mixture models of topic correlations
Wei Li and Andrew Mccallum
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Region-based value iteration for partially observable Markov decision processes
Hui Li, Xuejun Liao and Lawrence Carin
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Multiclass boosting with repartitioning
Ling Li
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Nonstationary kernel combination
Darrin P. Lewis, Tony Jebara and William S. Noble
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Efficient MAP approximation for dense energy functions
Marius Leordeanu and Martial Hebert
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

A probabilistic model for text kernels
Alain Lehmann and John Shawe-taylor
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Using query-specific variance estimates to combine Bayesian classifiers
Chi-hoon Lee, Russell Greiner and Shaojun Wang
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Simpler knowledge-based support vector machines
Quoc V. Le, Alex J. Smola and Thomas Gärtner
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Local distance preservation in the GP-LVM through back constraints
Neil D. Lawrence and Joaquin Q. Candela
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Learning low-rank kernel matrices
Brian Kulis, Mátyás A. Sustik and Inderjit S. Dhillon
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Data association for topic intensity tracking
Andreas Krause, Jure Leskovec and Carlos Guestrin
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Autonomous shaping: knowledge transfer in reinforcement learning
George Konidaris and Andrew G. Barto
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Fast particle smoothing: if I had a million particles
Mike Klaas, Mark Briers, Nando D. Freitas, Arnaud Doucet, Simon Maskell and Dustin Lang
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Pareto optimal linear classification
Seung-jean Kim, Alessandro Magnani, Sikandar Samar, Stephen P. Boyd and Johan Lim
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Optimal kernel selection in Kernel Fisher discriminant analysis
Seung-jean Kim, Alessandro Magnani and Stephen P. Boyd
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Personalized handwriting recognition via biased regularization
Wolf Kienzle and Kumar Chellapilla
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Automatic basis function construction for approximate dynamic programming and reinforcement learning
Philipp W. Keller, Shie Mannor and Doina Precup
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Estimating relatedness via data compression
Brendan Juba
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Hidden process models
Rebecca A. Hutchinson, Tom M. Mitchell and Indrayana Rustandi
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Ranking individuals by group comparisons
Tzu-kuo Huang, Chih-jen Lin and Ruby C. Weng
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Looping suffix tree-based inference of partially observable hidden state
Michael P. Holmes and Charles Jr.
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Batch mode active learning and its application to medical image classification
Steven Hoi, Rong Jin, Jianke Zhu and Michael R. Lyu
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Learning a kernel function for classification with small training samples
Tomer Hertz, Aharon Bar-hillel and Daphna Weinshall
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

An analysis of graph cut size for transductive learning
Steve Hanneke
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Fast transpose methods for kernel learning on sparse data
Patrick Haffner
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Practical solutions to the problem of diagonal dominance in kernel document clustering
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks
Alex Graves, Santiago Fernández, Faustino J. Gomez and Jürgen Schmidhuber
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

A choice model with infinitely many latent features
Dilan Görür, Frank Jäkel and Carl E. Rasmussen
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Nightmare at test time: robust learning by feature deletion
Amir Globerson and Sam T. Roweis
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Kernelizing the output of tree-based methods
Pierre Geurts, Louis Wehenkel and Florence D'alché-buc
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

The rate adapting poisson model for information retrieval and object recognition
Peter V. Gehler, Alex Holub and Max Welling
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

A note on mixtures of experts for multiclass responses: approximation rate and Consistent Bayesian Inference
Yang Ge and Wenxin Jiang
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Regression with the optimised combination technique
Jochen Garcke
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Online multiclass learning by interclass hypothesis sharing
Michael Fink, Shai Shalev-shwartz, Yoram Singer and Shimon Ullman
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Qualitative reinforcement learning
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

A graphical model for predicting protein molecular function
Barbara E. Engelhardt, Michael I. Jordan and Steven E. Brenner
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Clustering documents with an exponential-family approximation of the Dirichlet compound multinomial distribution
Charles Elkan
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

{\it R}$_{\mbox{1}}$-PCA: rotational invariant {\it L}$_{\mbox{1}}$-norm principal component analysis for robust subspace factorization
Chris Ding, Ding Zhou, Xiaofeng He and Hongyuan Zha
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Efficient learning of Naive Bayes classifiers under class-conditional classification noise
Françcois Denis, Christophe N. Magnan and Liva Ralaivola
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Learning the structure of Factored Markov Decision Processes in reinforcement learning problems
Thomas Degris, Olivier Sigaud and Pierre-henri Wuillemin
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Collaborative prediction using ensembles of Maximum Margin Matrix Factorizations
Dennis Decoste
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

The relationship between Precision-Recall and ROC curves
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Locally adaptive classification piloted by uncertainty
Juan Dai, Shuicheng Yan, Xiaoou Tang and James T. Kwok
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Learning algorithms for online principal-agent problems (and selling goods online)
Vincent Conitzer and Nikesh Garera
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Ronan Collobert, Fabian H. Sinz, Jason Weston and Léon Bottou
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

A regularization framework for multiple-instance learning
Pak-ming Cheung and James T. Kwok
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

A continuation method for semi-supervised SVMs
Olivier Chapelle, Mingmin Chi and Alexander Zien
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Hierarchical classification: combining Bayes with SVM
Nicolò Cesa-bianchi, Claudio Gentile and Luca Zaniboni
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Robust Euclidean embedding
Lawrence Cayton and Sanjoy Dasgupta
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

An empirical comparison of supervised learning algorithms
Rich Caruana and Alexandru Niculescu-mizil
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Fast nonparametric clustering with Gaussian blurring mean-shift
Miguel Á. Carreira-perpiñán
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Semi-supervised learning for structured output variables
Ulf Brefeld and Tobias Scheffer
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Efficient co-regularised least squares regression
Ulf Brefeld, Thomas Gärtner, Tobias Scheffer and Stefan Wrobel
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Learning predictive state representations using non-blind policies
Michael H. Bowling, Peter Mccracken, Michael James, James Neufeld and Dana F. Wilkinson
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Predictive search distributions
Edwin V. Bonilla, Christopher Williams, Felix V. Agakov, John Cavazos, John Thomson and Michael O'boyle
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Dynamic topic models
David M. Blei and John D. Lafferty
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Graph model selection using maximum likelihood
Ivona Bezáková, Adam Kalai and Rahul Santhanam
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Cover trees for nearest neighbor
Alina Beygelzimer, Sham Kakade and John Langford
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Convex optimization techniques for fitting sparse Gaussian graphical models
Onureena Banerjee, Laurent E. Ghaoui, Alexandre D'aspremont and Georges Natsoulis
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

On Bayesian bounds
Arindam Banerjee
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Agnostic active learning
Maria-florina Balcan, Alina Beygelzimer and John Langford
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

On a theory of learning with similarity functions
Maria-florina Balcan and Avrim Blum
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

A new approach to data driven clustering
Arik Azran and Zoubin Ghahramani
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Relational temporal difference learning
Nima Asgharbeygi, David J. Stracuzzi and Pat Langley
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

A DC-programming algorithm for kernel selection
Andreas Argyriou, Raphael Hauser, Charles A. Micchelli and Massimiliano Pontil
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Robust probabilistic projections
Cédric Archambeau, Nicolas Delannay and Michel Verleysen
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Algorithms for portfolio management based on the Newton method
Amit Agarwal, Elad Hazan, Satyen Kale and Robert E. Schapire
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Higher order learning with graphs
Sameer Agarwal, Kristin Branson and Serge Belongie
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Ranking on graph data
Shivani Agarwal
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Using inaccurate models in reinforcement learning
Pieter Abbeel, Morgan Quigley and Andrew Y. Ng
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006

Streamwise Feature Selection
Jing Zhou, Dean P. Foster, Robert A. Stine and Lyle H. Ungar
Journal of Machine Learning Research, 2006

On Model Selection Consistency of Lasso
Peng Zhao and Bin Yu
Journal of Machine Learning Research, 2006

Ensemble Pruning Via Semi-definite Programming
Yi Zhang, Samuel Burer and W. N. Street
Journal of Machine Learning Research, 2006

Parallel Software for Training Large Scale Support Vector Machines on Multiprocessor Systems
Luca Zanni, Thomas Serafini and Gaetano Zanghirati
Journal of Machine Learning Research, 2006

Computational and Theoretical Analysis of Null Space and Orthogonal Linear Discriminant Analysis
Jieping Ye and Tao Xiong
Journal of Machine Learning Research, 2006

Linear Programming Relaxations and Belief Propagation - An Empirical Study
Chen Yanover, Talya Meltzer and Yair Weiss
Journal of Machine Learning Research, 2006

A Direct Method for Building Sparse Kernel Learning Algorithms
Mingrui Wu, Bernhard Schölkopf and Gökhan H. Bakir
Journal of Machine Learning Research, 2006

On Inferring Application Protocol Behaviors in Encrypted Network Traffic
Charles V. Wright, Fabian Monrose and Gerald M. Masson
Journal of Machine Learning Research, 2006

Evolutionary Function Approximation for Reinforcement Learning
Shimon Whiteson and Peter Stone
Journal of Machine Learning Research, 2006

Stochastic Complexities of Gaussian Mixtures in Variational Bayesian Approximation
Kazuho Watanabe and Sumio Watanabe
Journal of Machine Learning Research, 2006

Estimating the "Wrong" Graphical Model: Benefits in the Computation-Limited Setting
Martin J. Wainwright
Journal of Machine Learning Research, 2006

Step Size Adaptation in Reproducing Kernel Hilbert Space
S. Vishwanathan, Nicol N. Schraudolph and Alex J. Smola
Journal of Machine Learning Research, 2006

Consistency and Convergence Rates of One-Class SVMs and Related Algorithms
Régis Vert and Jean-philippe Vert
Journal of Machine Learning Research, 2006

Structured Prediction, Dual Extragradient and Bregman Projections
Benjamin Taskar, Simon Lacoste-julien and Michael I. Jordan
Journal of Machine Learning Research, 2006

Nonparametric Quantile Estimation
Ichiro Takeuchi, Quoc V. Le, Tim D. Sears and Alex J. Smola
Journal of Machine Learning Research, 2006

Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error
Masashi Sugiyama
Journal of Machine Learning Research, 2006

Learning Image Components for Object Recognition
Michael W. Spratling
Journal of Machine Learning Research, 2006

Large Scale Multiple Kernel Learning
Sören Sonnenburg, Gunnar Rätsch, Christin Schäfer and Bernhard Schölkopf
Journal of Machine Learning Research, 2006

Noisy-OR Component Analysis and its Application to Link Analysis
Tomás Singliar and Milos Hauskrecht
Journal of Machine Learning Research, 2006

Learning the Structure of Linear Latent Variable Models
Ricardo Silva, Richard Scheines, Clark Glymour and Peter Spirtes
Journal of Machine Learning Research, 2006

Second Order Cone Programming Approaches for Handling Missing and Uncertain Data
Pannagadatta K. Shivaswamy, Chiranjib Bhattacharyya and Alex J. Smola
Journal of Machine Learning Research, 2006

A Linear Non-Gaussian Acyclic Model for Causal Discovery
Shohei Shimizu, Patrik O. Hoyer, Aapo Hyvärinen and Antti J. Kerminen
Journal of Machine Learning Research, 2006

Efficient Learning of Label Ranking by Soft Projections onto Polyhedra
Shai Shalev-shwartz and Yoram Singer
Journal of Machine Learning Research, 2006

Learning Minimum Volume Sets
Clayton Scott and Robert D. Nowak
Journal of Machine Learning Research, 2006

On the Complexity of Learning Lexicographic Strategies
Michael Schmitt and Laura Martignon
Journal of Machine Learning Research, 2006

An Efficient Implementation of an Active Set Method for SVMs
Katya Scheinberg
Journal of Machine Learning Research, 2006

A Hierarchy of Support Vector Machines for Pattern Detection
Hichem Sahbi and Donald Geman
Journal of Machine Learning Research, 2006

Pattern Recognition for Conditionally Independent Data
Daniil Ryabko
Journal of Machine Learning Research, 2006

A Graphical Representation of Equivalence Classes of AMP Chain Graphs
Alberto Roverato and Milan Studen\'y
Journal of Machine Learning Research, 2006

Kernel-Based Learning of Hierarchical Multilabel Classification Models
Juho Rousu, Craig Saunders, Sándor Szedmák and John Shawe-taylor
Journal of Machine Learning Research, 2006

Learning Parts-Based Representations of Data
David A. Ross and Richard S. Zemel
Journal of Machine Learning Research, 2006

Active Learning with Feedback on Features and Instances
Hema Raghavan, Omid Madani and Rosie Jones
Journal of Machine Learning Research, 2006

Point-Based Value Iteration for Continuous POMDPs
Josep M. Porta, Nikos A. Vlassis, Matthijs Spaan and Pascal Poupart
Journal of Machine Learning Research, 2006

MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals
Dana Pe'er, Amos Tanay and Aviv Regev
Journal of Machine Learning Research, 2006

Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting
Andrea Passerini, Paolo Frasconi and Luc D. Raedt
Journal of Machine Learning Research, 2006

Linear State-Space Models for Blind Source Separation
Rasmus K. Olsson and Lars K. Hansen
Journal of Machine Learning Research, 2006

Bayesian Network Learning with Parameter Constraints
Radu S. Niculescu, Tom M. Mitchell and R. B. Rao
Journal of Machine Learning Research, 2006

Temporal Coding using the Response Properties of Spiking Neurons
Thomas Voegtlin
Advances in Neural Information Processing Systems 19, 2006

Correcting Sample Selection Bias by Unlabeled Data
Jiayuan Huang, Arthur Gretton, Karsten M. Borgwardt, Bernhard Schölkopf and Alex J. Smola
Advances in Neural Information Processing Systems 19, 2006

Optimal Change-Detection and Spiking Neurons
Angela J. Yu
Advances in Neural Information Processing Systems 19, 2006

Clustering appearance and shape by learning jigsaws
Anitha Kannan, John Winn and Carsten Rother
Advances in Neural Information Processing Systems 19, 2006

Using Combinatorial Optimization within Max-Product Belief Propagation
Daniel Tarlow, Gal Elidan, Daphne Koller and John C. Duchi
Advances in Neural Information Processing Systems 19, 2006

Learning to parse images of articulated bodies
Deva Ramanan
Advances in Neural Information Processing Systems 19, 2006

Graph-Based Visual Saliency
Jonathan Harel, Christof Koch and Pietro Perona
Advances in Neural Information Processing Systems 19, 2006

Training Conditional Random Fields for Maximum Labelwise Accuracy
Samuel S. Gross, Olga Russakovsky, Chuong B. Do and Serafim Batzoglou
Advances in Neural Information Processing Systems 19, 2006

Distributed Inference in Dynamical Systems
Stanislav Funiak, Carlos Guestrin, Rahul Sukthankar and Mark A. Paskin
Advances in Neural Information Processing Systems 19, 2006

Ordinal Regression by Extended Binary Classification
Ling Li and Hsuan-tien Lin
Advances in Neural Information Processing Systems 19, 2006

Efficient sparse coding algorithms
Honglak Lee, Alexis Battle, Rajat Raina and Andrew Y. Ng
Advances in Neural Information Processing Systems 19, 2006

Scalable Discriminative Learning for Natural Language Parsing and Translation
Joseph Turian, Benjamin Wellington and I. D. Melamed
Advances in Neural Information Processing Systems 19, 2006

PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier
Alexandre Lacasse, François Laviolette, Mario Marchand, Pascal Germain and Nicolas Usunier
Advances in Neural Information Processing Systems 19, 2006

In-Network PCA and Anomaly Detection
Ling Huang, Xuanlong Nguyen, Minos Garofalakis, Michael I. Jordan, Anthony Joseph and Nina Taft
Advances in Neural Information Processing Systems 19, 2006

Advances in Neural Information Processing Systems 19, 2006

Theory and Dynamics of Perceptual Bistability
Paul R. Schrater and Rashmi Sundareswara
Advances in Neural Information Processing Systems 19, 2006

Recursive ICA
Honghao Shan, Lingyun Zhang and Garrison W. Cottrell
Advances in Neural Information Processing Systems 19, 2006

Efficient Structure Learning of Markov Networks using $L_1$-Regularization
Su-in Lee, Varun Ganapathi and Daphne Koller
Advances in Neural Information Processing Systems 19, 2006

Conditional Random Sampling: A Sketch-based Sampling Technique for Sparse Data
Ping Li, Kenneth W. Church and Trevor J. Hastie
Advances in Neural Information Processing Systems 19, 2006

An Application of Reinforcement Learning to Aerobatic Helicopter Flight
Pieter Abbeel, Adam Coates, Morgan Quigley and Andrew Y. Ng
Advances in Neural Information Processing Systems 19, 2006

Natural Actor-Critic for Road Traffic Optimisation
Silvia Richter, Douglas Aberdeen and Jin Yu
Advances in Neural Information Processing Systems 19, 2006

Automated Hierarchy Discovery for Planning in Partially Observable Environments
Laurent Charlin, Pascal Poupart and Romy Shioda
Advances in Neural Information Processing Systems 19, 2006

Near-Uniform Sampling of Combinatorial Spaces Using XOR Constraints
Carla P. Gomes, Ashish Sabharwal and Bart Selman
Advances in Neural Information Processing Systems 19, 2006

High-Dimensional Graphical Model Selection Using $\ell_1$-Regularized Logistic Regression
Martin J. Wainwright, John D. Lafferty and Pradeep K. Ravikumar
Advances in Neural Information Processing Systems 19, 2006

Analysis of Representations for Domain Adaptation
Shai Ben-david, John Blitzer, Koby Crammer and Fernando Pereira
Advances in Neural Information Processing Systems 19, 2006

Fast Computation of Graph Kernels
Karsten M. Borgwardt, Nicol N. Schraudolph and S.v.n. Vishwanathan
Advances in Neural Information Processing Systems 19, 2006

Unsupervised Regression with Applications to Nonlinear System Identification
Ali Rahimi and Ben Recht
Advances in Neural Information Processing Systems 19, 2006

Combining causal and similarity-based reasoning
Charles Kemp, Patrick Shafto, Allison Berke and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 19, 2006

iLSTD: Eligibility Traces and Convergence Analysis
Alborz Geramifard, Michael Bowling, Martin Zinkevich and Richard S. Sutton
Advances in Neural Information Processing Systems 19, 2006

Large Margin Multi-channel Analog-to-Digital Conversion with Applications to Neural Prosthesis
Amit Gore and Shantanu Chakrabartty
Advances in Neural Information Processing Systems 19, 2006

Bayesian Model Scoring in Markov Random Fields
Sridevi Parise and Max Welling
Advances in Neural Information Processing Systems 19, 2006

Fast Iterative Kernel PCA
Nicol N. Schraudolph, Simon Günter and S.v.n. Vishwanathan
Advances in Neural Information Processing Systems 19, 2006

Unsupervised Learning of a Probabilistic Grammar for Object Detection and Parsing
Yuanhao Chen, Long Zhu and Alan L. Yuille
Advances in Neural Information Processing Systems 19, 2006

Efficient Learning of Sparse Representations with an Energy-Based Model
Marc'aurelio Ranzato, Christopher Poultney, Sumit Chopra and Yann L. Cun
Advances in Neural Information Processing Systems 19, 2006

Nonlinear physically-based models for decoding motor-cortical population activity
Gregory Shakhnarovich, Sung-phil Kim and Michael J. Black
Advances in Neural Information Processing Systems 19, 2006

Multi-dynamic Bayesian Networks
Karim Filali and Jeff A. Bilmes
Advances in Neural Information Processing Systems 19, 2006

Large Margin Component Analysis
Lorenzo Torresani and Kuang-chih Lee
Advances in Neural Information Processing Systems 19, 2006

Single Channel Speech Separation Using Factorial Dynamics
John R. Hershey, Trausti Kristjansson, Steven Rennie and Peder A. Olsen
Advances in Neural Information Processing Systems 19, 2006

On the Relation Between Low Density Separation, Spectral Clustering and Graph Cuts
Hariharan Narayanan, Mikhail Belkin and Partha Niyogi
Advances in Neural Information Processing Systems 19, 2006

Prediction on a Graph with a Perceptron
Mark Herbster and Massimiliano Pontil
Advances in Neural Information Processing Systems 19, 2006

Kernels on Structured Objects Through Nested Histograms
Marco Cuturi and Kenji Fukumizu
Advances in Neural Information Processing Systems 19, 2006

A Theory of Retinal Population Coding
Eizaburo Doi and Michael S. Lewicki
Advances in Neural Information Processing Systems 19, 2006

Image Retrieval and Classification Using Local Distance Functions
Andrea Frome, Yoram Singer and Jitendra Malik
Advances in Neural Information Processing Systems 19, 2006

Sparse Representation for Signal Classification
Ke Huang and Selin Aviyente
Advances in Neural Information Processing Systems 19, 2006

Learning to Traverse Image Manifolds
Piotr Dollár, Vincent Rabaud and Serge J. Belongie
Advances in Neural Information Processing Systems 19, 2006

An Information Theoretic Framework for Eukaryotic Gradient Sensing
Joseph M. Kimmel, Richard M. Salter and Peter J. Thomas
Advances in Neural Information Processing Systems 19, 2006

Online Clustering of Moving Hyperplanes
René Vidal
Advances in Neural Information Processing Systems 19, 2006

Fast Discriminative Visual Codebooks using Randomized Clustering Forests
Frank Moosmann, Bill Triggs and Frederic Jurie
Advances in Neural Information Processing Systems 19, 2006

Greedy Layer-Wise Training of Deep Networks
Yoshua Bengio, Pascal Lamblin, Dan Popovici and Hugo Larochelle
Advances in Neural Information Processing Systems 19, 2006

Game Theoretic Algorithms for Protein-DNA binding
Luis Pérez-breva, Luis E. Ortiz, Chen-hsiang Yeang and Tommi S. Jaakkola
Advances in Neural Information Processing Systems 19, 2006

Map-Reduce for Machine Learning on Multicore
Cheng-tao Chu, Sang K. Kim, Yi-an Lin, Yuanyuan Yu, Gary Bradski, Kunle Olukotun and Andrew Y. Ng
Advances in Neural Information Processing Systems 19, 2006

Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral Space
Kyung-ah Sohn and Eric P. Xing
Advances in Neural Information Processing Systems 19, 2006

Modeling Dyadic Data with Binary Latent Factors
Edward Meeds, Zoubin Ghahramani, Radford M. Neal and Sam T. Roweis
Advances in Neural Information Processing Systems 19, 2006

Gaussian and Wishart Hyperkernels
Risi Kondor and Tony Jebara
Advances in Neural Information Processing Systems 19, 2006

Boosting Structured Prediction for Imitation Learning
J. A. Bagnell, Joel Chestnutt, David M. Bradley and Nathan D. Ratliff
Advances in Neural Information Processing Systems 19, 2006

Cross-Validation Optimization for Large Scale Hierarchical Classification Kernel Methods
Matthias Seeger
Advances in Neural Information Processing Systems 19, 2006

Clustering Under Prior Knowledge with Application to Image Segmentation
Dong S. Cheng, Vittorio Murino and Mário Figueiredo
Advances in Neural Information Processing Systems 19, 2006

Approximate inference using planar graph decomposition
Amir Globerson and Tommi S. Jaakkola
Advances in Neural Information Processing Systems 19, 2006

Detecting Humans via Their Pose
Alessandro Bissacco, Ming-hsuan Yang and Stefano Soatto
Advances in Neural Information Processing Systems 19, 2006

No-regret Algorithms for Online Convex Programs
Geoffrey J. Gordon
Advances in Neural Information Processing Systems 19, 2006

Modeling Human Motion Using Binary Latent Variables
Graham W. Taylor, Geoffrey E. Hinton and Sam T. Roweis
Advances in Neural Information Processing Systems 19, 2006

Part-based Probabilistic Point Matching using Equivalence Constraints
Graham Mcneill and Sethu Vijayakumar
Advances in Neural Information Processing Systems 19, 2006

Linearly-solvable Markov decision problems
Emanuel Todorov
Advances in Neural Information Processing Systems 19, 2006

TrueSkill™: A Bayesian Skill Rating System
Ralf Herbrich, Tom Minka and Thore Graepel
Advances in Neural Information Processing Systems 19, 2006

Computation of Similarity Measures for Sequential Data using Generalized Suffix Trees
Advances in Neural Information Processing Systems 19, 2006

Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization
Rey Ramírez, Jason Palmer, Scott Makeig, Bhaskar D. Rao and David P. Wipf
Advances in Neural Information Processing Systems 19, 2006

Shifting, One-Inclusion Mistake Bounds and Tight Multiclass Expected Risk Bounds
Benjamin I. Rubinstein, Peter L. Bartlett and J. H. Rubinstein
Advances in Neural Information Processing Systems 19, 2006

Recursive Attribute Factoring
Deepak Verma, Karl Pfleger and David Tax
Advances in Neural Information Processing Systems 19, 2006

Sample Complexity of Policy Search with Known Dynamics
Peter L. Bartlett and Ambuj Tewari
Advances in Neural Information Processing Systems 19, 2006

Relational Learning with Gaussian Processes
Wei Chu, Vikas Sindhwani, Zoubin Ghahramani and S. S. Keerthi
Advances in Neural Information Processing Systems 19, 2006

Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian Models
Alexander T. Ihler and Padhraic Smyth
Advances in Neural Information Processing Systems 19, 2006

Learning on Graph with Laplacian Regularization
Rie K. Ando and Tong Zhang
Advances in Neural Information Processing Systems 19, 2006

Stability of $K$-Means Clustering
Alexander Rakhlin and Andrea Caponnetto
Advances in Neural Information Processing Systems 19, 2006

Context dependent amplification of both rate and event-correlation in a VLSI network of spiking neurons
Elisabetta Chicca, Giacomo Indiveri and Rodney J. Douglas
Advances in Neural Information Processing Systems 19, 2006

MLLE: Modified Locally Linear Embedding Using Multiple Weights
Zhenyue Zhang and Jing Wang
Advances in Neural Information Processing Systems 19, 2006

Hierarchical Dirichlet Processes with Random Effects
Advances in Neural Information Processing Systems 19, 2006

Neurophysiological Evidence of Cooperative Mechanisms for Stereo Computation
Jason M. Samonds, Brian R. Potetz and Tai S. Lee
Advances in Neural Information Processing Systems 19, 2006

Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Models
Mark Johnson, Thomas L. Griffiths and Sharon Goldwater
Advances in Neural Information Processing Systems 19, 2006

A selective attention multi--chip system with dynamic synapses and spiking neurons
Chiara Bartolozzi and Giacomo Indiveri
Advances in Neural Information Processing Systems 19, 2006

Graph Laplacian Regularization for Large-Scale Semidefinite Programming
Kilian Q. Weinberger, Fei Sha, Qihui Zhu and Lawrence K. Saul
Advances in Neural Information Processing Systems 19, 2006

Learning with Hypergraphs: Clustering, Classification, and Embedding
Dengyong Zhou, Jiayuan Huang and Bernhard Schölkopf
Advances in Neural Information Processing Systems 19, 2006

Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields
Chi-hoon Lee, Shaojun Wang, Feng Jiao, Dale Schuurmans and Russell Greiner
Advances in Neural Information Processing Systems 19, 2006

Online Classification for Complex Problems Using Simultaneous Projections
Yonatan Amit, Shai Shalev-shwartz and Yoram Singer
Advances in Neural Information Processing Systems 19, 2006

Multiple Instance Learning for Computer Aided Diagnosis
Murat Dundar, Balaji Krishnapuram, R. B. Rao and Glenn M. Fung
Advances in Neural Information Processing Systems 19, 2006

Towards a general independent subspace analysis
Fabian J. Theis
Advances in Neural Information Processing Systems 19, 2006

Learning Nonparametric Models for Probabilistic Imitation
David B. Grimes, Daniel R. Rashid and Rajesh P. Rao
Advances in Neural Information Processing Systems 19, 2006

Non-rigid point set registration: Coherent Point Drift
Andriy Myronenko, Xubo Song and Miguel Á. Carreira-perpiñán
Advances in Neural Information Processing Systems 19, 2006

Mutagenetic tree Fisher kernel improves prediction of HIV drug resistance from viral genotype
Tobias Sing and Niko Beerenwinkel
Advances in Neural Information Processing Systems 19, 2006

Learnability and the doubling dimension
Yi Li and Philip M. Long
Advances in Neural Information Processing Systems 19, 2006

A Kernel Method for the Two-Sample-Problem
Arthur Gretton, Karsten M. Borgwardt, Malte Rasch, Bernhard Schölkopf and Alex J. Smola
Advances in Neural Information Processing Systems 19, 2006

Learning to Rank with Nonsmooth Cost Functions
Christopher J. Burges, Robert Ragno and Quoc V. Le
Advances in Neural Information Processing Systems 19, 2006

Sparse Kernel Orthonormalized PLS for feature extraction in large data sets
Jerónimo Arenas-garcía, Kaare B. Petersen and Lars K. Hansen
Advances in Neural Information Processing Systems 19, 2006

Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure
Jennifer Listgarten, Radford M. Neal, Sam T. Roweis, Rachel Puckrin and Sean Cutler
Advances in Neural Information Processing Systems 19, 2006

The Robustness-Performance Tradeoff in Markov Decision Processes
Huan Xu and Shie Mannor
Advances in Neural Information Processing Systems 19, 2006

Reducing Calibration Time For Brain-Computer Interfaces: A Clustering Approach
Matthias Krauledat, Michael Schröder, Benjamin Blankertz and Klaus-robert Müller
Advances in Neural Information Processing Systems 19, 2006

Learning annotated hierarchies from relational data
Daniel M. Roy, Charles Kemp, Vikash K. Mansinghka and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 19, 2006

An Approach to Bounded Rationality
Eli Ben-sasson, Ehud Kalai and Adam Kalai
Advances in Neural Information Processing Systems 19, 2006

Effects of Stress and Genotype on Meta-parameter Dynamics in Reinforcement Learning
Gediminas Lukšys, Jérémie Knüsel, Denis Sheynikhovich, Carmen Sandi and Wulfram Gerstner
Advances in Neural Information Processing Systems 19, 2006

Manifold Denoising
Matthias Hein and Markus Maier
Advances in Neural Information Processing Systems 19, 2006

Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension
Manfred K. Warmuth and Dima Kuzmin
Advances in Neural Information Processing Systems 19, 2006

Information Bottleneck for Non Co-Occurrence Data
Yevgeny Seldin, Noam Slonim and Naftali Tishby
Advances in Neural Information Processing Systems 19, 2006

Speakers optimize information density through syntactic reduction
T. F. Jaeger and Roger P. Levy
Advances in Neural Information Processing Systems 19, 2006

Temporal dynamics of information content carried by neurons in the primary visual cortex
Danko Nikolić, Stefan Haeusler, Wolf Singer and Wolfgang Maass
Advances in Neural Information Processing Systems 19, 2006

A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation
Yee W. Teh, David Newman and Max Welling
Advances in Neural Information Processing Systems 19, 2006

Aggregating Classification Accuracy across Time: Application to Single Trial EEG
Steven Lemm, Christin Schäfer and Gabriel Curio
Advances in Neural Information Processing Systems 19, 2006

PG-means: learning the number of clusters in data
Yu Feng and Greg Hamerly
Advances in Neural Information Processing Systems 19, 2006

Bayesian Ensemble Learning
Hugh A. Chipman, Edward I. George and Robert E. Mcculloch
Advances in Neural Information Processing Systems 19, 2006

Bayesian Image Super-resolution, Continued
Lyndsey C. Pickup, David P. Capel, Stephen J. Roberts and Andrew Zisserman
Advances in Neural Information Processing Systems 19, 2006

Particle Filtering for Nonparametric Bayesian Matrix Factorization
Frank Wood and Thomas L. Griffiths
Advances in Neural Information Processing Systems 19, 2006

Similarity by Composition
Oren Boiman and Michal Irani
Advances in Neural Information Processing Systems 19, 2006

Unified Inference for Variational Bayesian Linear Gaussian State-Space Models
David Barber and Silvia Chiappa
Advances in Neural Information Processing Systems 19, 2006

A PAC-Bayes Risk Bound for General Loss Functions
Pascal Germain, Alexandre Lacasse, François Laviolette and Mario Marchand
Advances in Neural Information Processing Systems 19, 2006

Approximate Correspondences in High Dimensions
Kristen Grauman and Trevor Darrell
Advances in Neural Information Processing Systems 19, 2006

Parameter Expanded Variational Bayesian Methods
Tommi S. Jaakkola and Yuan Qi
Advances in Neural Information Processing Systems 19, 2006

A Nonparametric Approach to Bottom-Up Visual Saliency
Wolf Kienzle, Felix A. Wichmann, Matthias O. Franz and Bernhard Schölkopf
Advances in Neural Information Processing Systems 19, 2006

Dirichlet-Enhanced Spam Filtering based on Biased Samples
Steffen Bickel and Tobias Scheffer
Advances in Neural Information Processing Systems 19, 2006

Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning
Peter Auer and Ronald Ortner
Advances in Neural Information Processing Systems 19, 2006

Generalized Regularized Least-Squares Learning with Predefined Features in a Hilbert Space
Wenye Li, Kin-hong Lee and Kwong-sak Leung
Advances in Neural Information Processing Systems 19, 2006

A Switched Gaussian Process for Estimating Disparity and Segmentation in Binocular Stereo
Oliver Williams
Advances in Neural Information Processing Systems 19, 2006

Learning to be Bayesian without Supervision
Martin Raphan and Eero P. Simoncelli
Advances in Neural Information Processing Systems 19, 2006

The Neurodynamics of Belief Propagation on Binary Markov Random Fields
Thomas Ott and Ruedi Stoop
Advances in Neural Information Processing Systems 19, 2006

Learning from Multiple Sources
Koby Crammer, Michael Kearns and Jennifer Wortman
Advances in Neural Information Processing Systems 19, 2006

Learning Motion Style Synthesis from Perceptual Observations
Lorenzo Torresani, Peggy Hackney and Christoph Bregler
Advances in Neural Information Processing Systems 19, 2006

Sandeep Pandey and Christopher Olston
Advances in Neural Information Processing Systems 19, 2006

Simplifying Mixture Models through Function Approximation
Kai Zhang and James T. Kwok
Advances in Neural Information Processing Systems 19, 2006

Stochastic Relational Models for Discriminative Link Prediction
Kai Yu, Wei Chu, Shipeng Yu, Volker Tresp and Zhao Xu
Advances in Neural Information Processing Systems 19, 2006

Large-Scale Sparsified Manifold Regularization
Ivor W. Tsang and James T. Kwok
Advances in Neural Information Processing Systems 19, 2006

Attentional Processing on a Spike-Based VLSI Neural Network
Yingxue Wang, Rodney J. Douglas and Shih-chii Liu
Advances in Neural Information Processing Systems 19, 2006

A Local Learning Approach for Clustering
Mingrui Wu and Bernhard Schölkopf
Advances in Neural Information Processing Systems 19, 2006

Efficient Methods for Privacy Preserving Face Detection
Shai Avidan and Moshe Butman
Advances in Neural Information Processing Systems 19, 2006

Nonnegative Sparse PCA
Ron Zass and Amnon Shashua
Advances in Neural Information Processing Systems 19, 2006

Blind source separation for over-determined delayed mixtures
Lars Omlor and Martin Giese
Advances in Neural Information Processing Systems 19, 2006

Denoising and Dimension Reduction in Feature Space
Mikio L. Braun, Klaus-robert Müller and Joachim M. Buhmann
Advances in Neural Information Processing Systems 19, 2006

Context Effects in Category Learning: An Investigation of Four Probabilistic Models
Michael C. Mozer, Michael Shettel and Michael P. Holmes
Advances in Neural Information Processing Systems 19, 2006

Subordinate class recognition using relational object models
Aharon B. Hillel and Daphna Weinshall
Advances in Neural Information Processing Systems 19, 2006

Isotonic Conditional Random Fields and Local Sentiment Flow
Yi Mao and Guy Lebanon
Advances in Neural Information Processing Systems 19, 2006

Optimal Single-Class Classification Strategies
Ran El-yaniv and Mordechai Nisenson
Advances in Neural Information Processing Systems 19, 2006

S. S. Keerthi, Vikas Sindhwani and Olivier Chapelle
Advances in Neural Information Processing Systems 19, 2006

Learning Structural Equation Models for fMRI
Enrico Simonotto, Heather Whalley, Stephen Lawrie, Lawrence Murray, David Mcgonigle and Amos J. Storkey
Advances in Neural Information Processing Systems 19, 2006

Tighter PAC-Bayes Bounds
Advances in Neural Information Processing Systems 19, 2006

A Kernel Subspace Method by Stochastic Realization for Learning Nonlinear Dynamical Systems
Yoshinobu Kawahara, Takehisa Yairi and Kazuo Machida
Advances in Neural Information Processing Systems 19, 2006

Branch and Bound for Semi-Supervised Support Vector Machines
Olivier Chapelle, Vikas Sindhwani and S. S. Keerthi
Advances in Neural Information Processing Systems 19, 2006

Multi-Instance Multi-Label Learning with Application to Scene Classification
Zhi-hua Zhou and Min-ling Zhang
Advances in Neural Information Processing Systems 19, 2006

Emergence of conjunctive visual features by quadratic independent component analysis
J.t. Lindgren and Aapo Hyvärinen
Advances in Neural Information Processing Systems 19, 2006

Mixture Regression for Covariate Shift
Masashi Sugiyama and Amos J. Storkey
Advances in Neural Information Processing Systems 19, 2006

Logistic Regression for Single Trial EEG Classification
Ryota Tomioka, Kazuyuki Aihara and Klaus-robert Müller
Advances in Neural Information Processing Systems 19, 2006

Inducing Metric Violations in Human Similarity Judgements
Julian Laub, Klaus-robert Müller, Felix A. Wichmann and Jakob H. Macke
Advances in Neural Information Processing Systems 19, 2006

A Small World Threshold for Economic Network Formation
Eyal Even-dar and Michael Kearns
Advances in Neural Information Processing Systems 19, 2006

Active learning for misspecified generalized linear models
Francis R. Bach
Advances in Neural Information Processing Systems 19, 2006

A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments
Daniel J. Navarro and Thomas L. Griffiths
Advances in Neural Information Processing Systems 19, 2006

Blind Motion Deblurring Using Image Statistics
Anat Levin
Advances in Neural Information Processing Systems 19, 2006

Modeling General and Specific Aspects of Documents with a Probabilistic Topic Model
Chaitanya Chemudugunta, Padhraic Smyth and Mark Steyvers
Advances in Neural Information Processing Systems 19, 2006

Support Vector Machines on a Budget
Ofer Dekel and Yoram Singer
Advances in Neural Information Processing Systems 19, 2006

Convex Repeated Games and Fenchel Duality
Shai Shalev-shwartz and Yoram Singer
Advances in Neural Information Processing Systems 19, 2006

Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm
Robert Jenssen, Torbjørn Eltoft, Mark Girolami and Deniz Erdogmus
Advances in Neural Information Processing Systems 19, 2006

Learning Dense 3D Correspondence
Florian Steinke, Volker Blanz and Bernhard Schölkopf
Advances in Neural Information Processing Systems 19, 2006

A Bayesian Approach to Diffusion Models of Decision-Making and Response Time
Michael D. Lee, Ian G. Fuss and Daniel J. Navarro
Advances in Neural Information Processing Systems 19, 2006

Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks
Alexis Battle, Gal Chechik and Daphne Koller
Advances in Neural Information Processing Systems 19, 2006

Generalized Maximum Margin Clustering and Unsupervised Kernel Learning
Advances in Neural Information Processing Systems 19, 2006

implicit Online Learning with Kernels
Li Cheng, Dale Schuurmans, Shaojun Wang, Terry Caelli and S.v.n. Vishwanathan
Advances in Neural Information Processing Systems 19, 2006

Analysis of Contour Motions
Ce Liu, William T. Freeman and Edward H. Adelson
Advances in Neural Information Processing Systems 19, 2006

Real-time adaptive information-theoretic optimization of neurophysiology experiments
Jeremy Lewi, Robert Butera and Liam Paninski
Advances in Neural Information Processing Systems 19, 2006

On Transductive Regression
Corinna Cortes and Mehryar Mohri
Advances in Neural Information Processing Systems 19, 2006

Doubly Stochastic Normalization for Spectral Clustering
Ron Zass and Amnon Shashua
Advances in Neural Information Processing Systems 19, 2006

Andreas Argyriou, Theodoros Evgeniou and Massimiliano Pontil
Advances in Neural Information Processing Systems 19, 2006

Accelerated Variational Dirichlet Process Mixtures
Kenichi Kurihara, Max Welling and Nikos A. Vlassis
Advances in Neural Information Processing Systems 19, 2006

Inferring Network Structure from Co-Occurrences
Michael G. Rabbat, Mário Figueiredo and Robert Nowak
Advances in Neural Information Processing Systems 19, 2006

A Humanlike Predictor of Facial Attractiveness
Amit Kagian, Gideon Dror, Tommer Leyvand, Daniel Cohen-or and Eytan Ruppin
Advances in Neural Information Processing Systems 19, 2006

A Scalable Machine Learning Approach to Go
Lin Wu and Pierre F. Baldi
Advances in Neural Information Processing Systems 19, 2006

Geometric entropy minimization (GEM) for anomaly detection and localization
Alfred O. Hero
Advances in Neural Information Processing Systems 19, 2006

Sparse Multinomial Logistic Regression via Bayesian L1 Regularisation
Gavin C. Cawley, Nicola L. Talbot and Mark Girolami
Advances in Neural Information Processing Systems 19, 2006

Data Integration for Classification Problems Employing Gaussian Process Priors
Mark Girolami and Mingjun Zhong
Advances in Neural Information Processing Systems 19, 2006

Uncertainty, phase and oscillatory hippocampal recall
Máté Lengyel and Peter Dayan
Advances in Neural Information Processing Systems 19, 2006

An EM Algorithm for Localizing Multiple Sound Sources in Reverberant Environments
Michael I. Mandel, Daniel P. Ellis and Tony Jebara
Advances in Neural Information Processing Systems 19, 2006

Adaptive Spatial Filters with predefined Region of Interest for EEG based Brain-Computer-Interfaces
Moritz Grosse-wentrup, Klaus Gramann and Martin Buss
Advances in Neural Information Processing Systems 19, 2006

Peter L. Bartlett and Mikhail Traskin
Advances in Neural Information Processing Systems 19, 2006

A Complexity-Distortion Approach to Joint Pattern Alignment
Andrea Vedaldi and Stefano Soatto
Advances in Neural Information Processing Systems 19, 2006

Robotic Grasping of Novel Objects
Ashutosh Saxena, Justin Driemeyer, Justin Kearns and Andrew Y. Ng
Advances in Neural Information Processing Systems 19, 2006

Predicting spike times from subthreshold dynamics of a neuron
Ryota Kobayashi and Shigeru Shinomoto
Advances in Neural Information Processing Systems 19, 2006

Convergence of Laplacian Eigenmaps
Mikhail Belkin and Partha Niyogi
Advances in Neural Information Processing Systems 19, 2006

Stratification Learning: Detecting Mixed Density and Dimensionality in High Dimensional Point Clouds
Gloria Haro, Gregory Randall and Guillermo Sapiro
Advances in Neural Information Processing Systems 19, 2006

Balanced Graph Matching
Timothee Cour, Praveen Srinivasan and Jianbo Shi
Advances in Neural Information Processing Systems 19, 2006

An Oracle Inequality for Clipped Regularized Risk Minimizers
Ingo Steinwart, Don Hush and Clint Scovel
Advances in Neural Information Processing Systems 19, 2006

A Probabilistic Algorithm Integrating Source Localization and Noise Suppression of MEG and EEG data
Johanna M. Zumer, Hagai T. Attias, Kensuke Sekihara and Srikantan S. Nagarajan
Advances in Neural Information Processing Systems 19, 2006

Multi-Robot Negotiation: Approximating the Set of Subgame Perfect Equilibria in General-Sum Stochastic Games
Chris Murray and Geoffrey J. Gordon
Advances in Neural Information Processing Systems 19, 2006

Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions
Christian Walder, Olivier Chapelle and Bernhard Schölkopf
Advances in Neural Information Processing Systems 19, 2006

Attribute-efficient learning of decision lists and linear threshold functions under unconcentrated distributions
Philip M. Long and Rocco Servedio
Advances in Neural Information Processing Systems 19, 2006

A Novel Gaussian Sum Smoother for Approximate Inference in Switching Linear Dynamical Systems
David Barber and Bertrand Mesot
Advances in Neural Information Processing Systems 19, 2006

Large Scale Hidden Semi-Markov SVMs
Gunnar Rätsch and Sören Sonnenburg
Advances in Neural Information Processing Systems 19, 2006

Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms
Xinhua Zhang and Wee S. Lee
Advances in Neural Information Processing Systems 19, 2006

Differential Entropic Clustering of Multivariate Gaussians
Jason V. Davis and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 19, 2006

Statistical Modeling of Images with Fields of Gaussian Scale Mixtures
Siwei Lyu and Eero P. Simoncelli
Advances in Neural Information Processing Systems 19, 2006

Large Margin Hidden Markov Models for Automatic Speech Recognition
Fei Sha and Lawrence K. Saul
Advances in Neural Information Processing Systems 19, 2006

A recipe for optimizing a time-histogram
Hideaki Shimazaki and Shigeru Shinomoto
Advances in Neural Information Processing Systems 19, 2006

Fundamental Limitations of Spectral Clustering
Advances in Neural Information Processing Systems 19, 2006

Comparative Gene Prediction using Conditional Random Fields
Jade P. Vinson, David Decaprio, Matthew D. Pearson, Stacey Luoma and James E. Galagan
Advances in Neural Information Processing Systems 19, 2006

Modelling transcriptional regulation using Gaussian Processes
Neil D. Lawrence, Guido Sanguinetti and Magnus Rattray
Advances in Neural Information Processing Systems 19, 2006

Max-margin classification of incomplete data
Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel and Daphne Koller
Advances in Neural Information Processing Systems 19, 2006

Chained Boosting
Christian R. Shelton, Wesley Huie and Kin F. Kan
Advances in Neural Information Processing Systems 19, 2006

Multiple timescales and uncertainty in motor adaptation
Advances in Neural Information Processing Systems 19, 2006

Causal inference in sensorimotor integration
Konrad P. Körding and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 19, 2006

Conditional mean field
Peter Carbonetto and Nando D. Freitas
Advances in Neural Information Processing Systems 19, 2006

Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons
Stefan Klampfl, Wolfgang Maass and Robert A. Legenstein
Advances in Neural Information Processing Systems 19, 2006

Dynamic Foreground/Background Extraction from Images and Videos using Random Patches
Le Lu and Gregory D. Hager
Advances in Neural Information Processing Systems 19, 2006

Rémi Munos
Journal of Machine Learning Research, 2006

Geometric Variance Reduction in Markov Chains: Application to Value Function and Gradient Estimation
Rémi Munos
Journal of Machine Learning Research, 2006

Sayan Mukherjee and Ding-xuan Zhou
Journal of Machine Learning Research, 2006

Estimation of Gradients and Coordinate Covariation in Classification
Sayan Mukherjee and Qiang Wu
Journal of Machine Learning Research, 2006

On Representing and Generating Kernels by Fuzzy Equivalence Relations
Bernhard Moser
Journal of Machine Learning Research, 2006

Universal Kernels
Charles A. Micchelli, Yuesheng Xu and Haizhang Zhang
Journal of Machine Learning Research, 2006

Quantile Regression Forests
Nicolai Meinshausen
Journal of Machine Learning Research, 2006

Andreas Maurer
Journal of Machine Learning Research, 2006

Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization
Olvi L. Mangasarian
Journal of Machine Learning Research, 2006

Walk-Sums and Belief Propagation in Gaussian Graphical Models
Dmitry M. Malioutov, Jason K. Johnson and Alan S. Willsky
Journal of Machine Learning Research, 2006

New Algorithms for Efficient High-Dimensional Nonparametric Classification
Ting Liu, Andrew W. Moore and Alexander G. Gray
Journal of Machine Learning Research, 2006

Infinite-sigma Limits For Tikhonov Regularization
Ross A. Lippert and Ryan M. Rifkin
Journal of Machine Learning Research, 2006

Lower Bounds and Aggregation in Density Estimation
Guillaume Lecué
Journal of Machine Learning Research, 2006

Incremental Support Vector Learning: Analysis, Implementation and Applications
Pavel Laskov, Christian Gehl, Stefan Krüger and Klaus-robert Müller
Journal of Machine Learning Research, 2006

Learning Recursive Control Programs from Problem Solving
Pat Langley and Dongkyu Choi
Journal of Machine Learning Research, 2006

Learning to Detect and Classify Malicious Executables in the Wild
Jeremy Z. Kolter and Marcus A. Maloof
Journal of Machine Learning Research, 2006

Collaborative Multiagent Reinforcement Learning by Payoff Propagation
Jelle R. Kok and Nikos A. Vlassis
Journal of Machine Learning Research, 2006

Toward Attribute Efficient Learning of Decision Lists and Parities
Adam R. Klivans and Rocco A. Servedio
Journal of Machine Learning Research, 2006

Inductive Synthesis of Functional Programs: An Explanation Based Generalization Approach
Emanuel Kitzelmann and Ute Schmid
Journal of Machine Learning Research, 2006

Segmental Hidden Markov Models with Random Effects for Waveform Modeling
Journal of Machine Learning Research, 2006

Building Support Vector Machines with Reduced Classifier Complexity
S. S. Keerthi, Olivier Chapelle and Dennis Decoste
Journal of Machine Learning Research, 2006

Distance Patterns in Structural Similarity
Thomas Kämpke
Journal of Machine Learning Research, 2006

Causal Graph Based Decomposition of Factored MDPs
Anders Jonsson and Andrew G. Barto
Journal of Machine Learning Research, 2006

QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines
Don R. Hush, Patrick Kelly, Clint Scovel and Ingo Steinwart
Journal of Machine Learning Research, 2006

Generalized Bradley-Terry Models and Multi-Class Probability Estimates
Tzu-kuo Huang, Ruby C. Weng and Chih-jen Lin
Journal of Machine Learning Research, 2006

Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming
Matthias Heiler and Christoph Schnörr
Journal of Machine Learning Research, 2006

Using Machine Learning to Guide Architecture Simulation
Greg Hamerly, Erez Perelman, Jeremy Lau, Brad Calder and Timothy Sherwood
Journal of Machine Learning Research, 2006

Some Discriminant-Based PAC Algorithms
Paul W. Goldberg
Journal of Machine Learning Research, 2006

Maximum-Gain Working Set Selection for SVMs
Tobias Glasmachers and Christian Igel
Journal of Machine Learning Research, 2006

One-Class Novelty Detection for Seizure Analysis from Intracranial EEG
Andrew B. Gardner, Abba M. Krieger, George J. Vachtsevanos and Brian Litt
Journal of Machine Learning Research, 2006

Spam Filtering Based On The Analysis Of Text Information Embedded Into Images
Giorgio Fumera, Ignazio Pillai and Fabio Roli
Journal of Machine Learning Research, 2006

Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems
Eyal Even-dar, Shie Mannor and Yishay Mansour
Journal of Machine Learning Research, 2006

Bounds for the Loss in Probability of Correct Classification Under Model Based Approximation
Magnus Ekdahl and Timo Koski
Journal of Machine Learning Research, 2006

Statistical Comparisons of Classifiers over Multiple Data Sets
Janez Demsar
Journal of Machine Learning Research, 2006

Online Passive-Aggressive Algorithms
Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-shwartz and Yoram Singer
Journal of Machine Learning Research, 2006

Large Scale Transductive SVMs
Ronan Collobert, Fabian H. Sinz, Jason Weston and Léon Bottou
Journal of Machine Learning Research, 2006

Rearrangement Clustering: Pitfalls, Remedies, and Applications
Sharlee Climer and Weixiong Zhang
Journal of Machine Learning Research, 2006

Consistency of Multiclass Empirical Risk Minimization Methods Based on Convex Loss
Di-rong Chen and Tao Sun
Journal of Machine Learning Research, 2006

Adaptive Prototype Learning Algorithms: Theoretical and Experimental Studies
Fu Chang, Chin-chin Lin and Chi-jen Lu
Journal of Machine Learning Research, 2006

Machine Learning for Computer Security
Philip K. Chan and Richard Lippmann
Journal of Machine Learning Research, 2006

Worst-Case Analysis of Selective Sampling for Linear Classification
Nicolò Cesa-bianchi, Claudio Gentile and Luca Zaniboni
Journal of Machine Learning Research, 2006

Incremental Algorithms for Hierarchical Classification
Nicolò Cesa-bianchi, Claudio Gentile and Luca Zaniboni
Journal of Machine Learning Research, 2006

Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
Tonatiuh P. Centeno and Neil D. Lawrence
Journal of Machine Learning Research, 2006

A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
Enrique F. Castillo, Bertha Guijarro-berdiñas, Oscar Fontenla-romero and Amparo Alonso-betanzos
Journal of Machine Learning Research, 2006

A Robust Procedure For Gaussian Graphical Model Search From Microarray Data With {\it p} Larger Than {\it n}
Robert Castelo and Alberto Roverato
Journal of Machine Learning Research, 2006

Stability Properties of Empirical Risk Minimization over Donsker Classes
Andrea Caponnetto and Alexander Rakhlin
Journal of Machine Learning Research, 2006

A Scoring Function for Learning Bayesian Networks based on Mutual Information and Conditional Independence Tests
Luis Campos
Journal of Machine Learning Research, 2006

Sparse Boosting
Peter Bühlmann and Bin Yu
Journal of Machine Learning Research, 2006

Accurate Error Bounds for the Eigenvalues of the Kernel Matrix
Mikio L. Braun
Journal of Machine Learning Research, 2006

Spam Filtering Using Statistical Data Compression Models
Andrej Bratko, Gordon V. Cormack, Bogdan Filipic, Thomas R. Lynam and Blaz Zupan
Journal of Machine Learning Research, 2006

In Search of Non-Gaussian Components of a High-Dimensional Distribution
Gilles Blanchard, Motoaki Kawanabe, Masashi Sugiyama, Vladimir Spokoiny and Klaus-robert Müller
Journal of Machine Learning Research, 2006

Fast SDP Relaxations of Graph Cut Clustering, Transduction, and Other Combinatorial Problem
Tijl D. Bie and Nello Cristianini
Journal of Machine Learning Research, 2006

Some Theory for Generalized Boosting Algorithms
Peter J. Bickel, Yaacov Ritov and Alon Zakai
Journal of Machine Learning Research, 2006

A Simulation-Based Algorithm for Ergodic Control of Markov Chains Conditioned on Rare Events
Shalabh Bhatnagar, Vivek S. Borkar and Madhukar Akarapu
Journal of Machine Learning Research, 2006

Linear Programs for Hypotheses Selection in Probabilistic Inference Models
Anders Bergkvist, Peter Damaschke and Marcel Lüthi
Journal of Machine Learning Research, 2006

The Interplay of Optimization and Machine Learning Research
Kristin P. Bennett and Emilio Parrado-hernández
Journal of Machine Learning Research, 2006

Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
Mikhail Belkin, Partha Niyogi and Vikas Sindhwani
Journal of Machine Learning Research, 2006

Superior Guarantees for Sequential Prediction and Lossless Compression via Alphabet Decomposition
Ron Begleiter and Ran El-yaniv
Journal of Machine Learning Research, 2006

Expectation Correction for Smoothed Inference in Switching Linear Dynamical Systems
David Barber
Journal of Machine Learning Research, 2006

Learning Spectral Clustering, With Application To Speech Separation
Francis R. Bach and Michael I. Jordan
Journal of Machine Learning Research, 2006

Considering Cost Asymmetry in Learning Classifiers
Francis R. Bach, David Heckerman and Eric Horvitz
Journal of Machine Learning Research, 2006

Learning a Hidden Hypergraph
Dana Angluin and Jiang Chen
Journal of Machine Learning Research, 2006

Learning Factor Graphs in Polynomial Time and Sample Complexity
Pieter Abbeel, Daphne Koller and Andrew Y. Ng
Journal of Machine Learning Research, 2006