Exploration and Apprenticeship Learning in Reinforcement Learning |

Pieter Abbeel, Andrew Y. Ng |

Active Learning for Hidden Markov Models: Objective Functions and Algorithms |

Brigham Anderson, Andrew Moore |

Tempering for Bayesian C&RT |

Nicos Angelopoulos, James Cussens |

Fast Condensed Nearest Neighbor Rule |

Fabrizio Angiulli |

Predictive low-rank decomposition for kernel methods |

Francis R. Bach, Michael I. Jordan |

Multi-Way Distributional Clustering via Pairwise Interactions |

Ron Bekkerman, Ran El-Yaniv, Andrew McCallum |

Error Limiting Reductions Between Classification Tasks |

Alina Beygelzimer, Varsha Dani, Tom Hayes, John Langford, Bianca Zadrozny |

Multi-Instance Tree Learning |

Hendrik Blockeel, David Page, Ashwin Srinivasan |

Action Respecting Embedding |

Michael Bowling, Ali Ghodsi, Dana Wilkinson |

Clustering Through Ranking On Manifolds |

Markus Breitenbach, Gregory Z. Grudic |

Reducing Overfitting in Process Model Induction |

Will Bridewell, Narges Bani Asani, Pat Langley, Ljupco Todorovski |

Learning to Rank using Gradient Descent |

Chris Burges,Tal Shaked, Erin Renshaw, Ari Lazier, Matt Deeds, Nicole Hamilton, Greg Hullender |

Learning Class-Discriminative Dynamic Bayesian Networks |

John Burge, Terran Lane |

Recognition and Reproduction of Gestures using a Probabilistic Framework combining PCA, ICA and HMM |

Sylvain Calinon, Aude Billard |

Predicting Probability Distributions for Surf Height Using an Ensemble of Mixture Density Networks |

Michael Carney, Padraig Cunningham, Jim Dowling, Ciaran Lee |

Hedged learning: Regret minimization with learning experts |

Yu-Han Chang, Leslie Kaelbling |

Variational Bayesian Image Modelling |

Li Cheng, Feng Jiao, Dale Schuurmans, Shaojun Wang |

Preference Learning with Gaussian Processes |

Wei Chu, Zoubin Ghahramani |

New Approaches to Support Vector Ordinal Regression |

Wei Chu, S. Sathiya Keerthi |

A General Regression Technique for Learning Transductions |

Corinna Cortes, Mehryar Mohri, Jason Weston |

Learning to Compete, Compromise, and Cooperate in Repeated General-Sum Games |

Jacob W. Crandal, Michael A. Goodrich |

Learning as Search Optimization: Approximate Large Margin Methods for Structured Prediction |

Hal Daume III, Daniel Marcu |

Multimodal Oriented Discriminant Analysis |

Fernando De la Torre, Takeo Kanade |

A Practical Generalization of Fourier-based Learning |

Adam Drake, Dan Ventura |

Combining Model-Based and Instance-Based Learning for First Order Regression |

Kurt Driessens, Saso Dzeroski |

Reinforcement learning with Gaussian processes |

Yaakov Engel, Shie Mannor, Ron Meir |

Experimental Comparison between Bagging and Monte Carlo Ensemble Classification |

Roberto Esposito, Lorenza Saitta |

Supervised Clustering with Support Vector Machines |

Thomas Finley, Thorsten Joachims |

Optimal Assignment Kernels For Attributed Molecular Graphs |

Holger Fröhlich, Jörg Wegner, Florian Sieker, Andreas Zell |

Closed-form dual perturb and combine for tree-based models |

Pierre Geurts, Louis Wehenkel |

Hierarchic Bayesian Models for Kernel Learning |

Mark Girolami, Simon Rogers |

Online Feature Selection for Pixel Classification |

Karen Glocer, Damian Eads, James Theiler |

Learning Strategies for Story Comprehension: A Reinforcement Learning Approach |

Eugene Grois, David C. Wilkins |

Near-Optimal Sensor Placements in Gaussian Processes |

Carlos Guestrin, Andreas Krause, Ajit Pauk Singh |

Robust One-Class Clustering Using Hybrid Global and Local Search |

Gunjan Gupta, Joydeep Ghosh |

Statistical and Computational Analysis of Locality Preserving Projection |

Xiaofei He, Deng Cai, Wanli Min |

Intrinsic Dimensionality Estimation of Submanifolds in (d |

Matthias Hein, Jean-Yves Audibert |

Bayesian Hierarchical Clustering |

Katherine Heller, Zoubin Ghahramani |

Online Learning over Graphs |

Mark Herbster, Massimiliano Pontil, Lisa Wainer |

Adapting Two-Class Classification Methods to Many Class Problems |

Simon I. Hill, Arnaud Doucet |

A Martingale Framework for Concept Change Detection in Time-Varying Data Streams |

Shen-Shyang Ho |

Multi-Class protein fold detection using adaptive codes |

Eugene Ie, Jason Weston, William Stafford Noble, Christina Leslie |

Learning Approximate Preconditions for Methods in Hierarchical Plans |

Okhtay Ilghami, Héctor Muñoz-Avila, Dana S. Nau, David W. Aha |

Evaluating Machine Learning for Information Extraction |

Neil Ireson, Fabio Ciravegna, Mary Elaine Califf, Dayne Freitag, Nicholas Kushmerick, Alberto Lavelli |

Learn to Weight Terms in Information Retrieval Using Category Information |

Rong Jin, Joyce Y. Chai, Luo Si |

A Smoothed Boosting Algorithm Using Probabilistic Output Codes |

Rong Jin, Jian Zhang |

Efficient discriminative learning of Bayesian network classifier via Boosted Augmented Naive Bayes |

Yushi Jing, Vladimir Pavlovic, James M. Rehg |

A Support Vector Method for Multivariate Performance Measures |

Thorsten Joachims |

Error Bounds for Correlation Clustering |

Thorsten Joachims, John Hopcroft |

Interactive Learning of Mappings from Visual Percepts to Actions |

Sébastien Jodogne, Justus H. Piater |

A Causal Approach to Hierarchical Decomposition of Factored MDPs |

Anders Jonsson, Andrew Barto |

A Comparison of Tight Generalization Error Bounds |

Matti Kääriäinen, John Langford |

Generalized LARS as an Effective Feature Selection Tool for Text Classification With SVMs |

S. Sathiya Keerthi |

Ensembles of Biased Classifiers |

Rinat Khoussainov, Andreas Hess, Nicholas Kushmerick |

Computational Aspects of Bayesian Partition Models |

Mikko Koivisto, Kismat Sood |

Learning the Structure of Markov Logic Networks |

Stanley Kok, Pedro Domingos |

Using Additive Expert Ensembles to Cope with Concept Drift |

Jeremy Kolter, Marcus Maloof |

Semi-supervised Graph Clustering: A Kernel Approach |

Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Raymond J. Mooney |

A Brain Computer Interface with Online Feedback based on Magnetoencephalography |

Thomas Navin Lal, Michael Schröder, N. Jeremy Hill, Hubert Preissl, Thilo Hinterberger, Jürgen Mellinger, Martin Bogdan, Wolfgang Rosenstiel, Thomas, Hofmann, Niels Birbaumer, Bernhard Schölkopf |

Relating Reinforcement Learning Performance to Classification Performance |

John Langford, Bianca Zadrozny |

PAC-Bayes Risk Bounds for Sample-Compressed Gibbs Classifiers |

François Laviolette, Mario Marchand |

Heteroscedastic Gaussian Process Regression |

Quoc V. Le, Alex J. Smola, Stéphane Canu |

Predicting Relative Performance of Classifiers from Samples |

Rui Leite, Pavel Brazdil |

Logistic Regression with an Auxiliary Data Source |

Xuejun Liao, Ya Xue, Lawrence Carin |

Predicting Protein Folds with Structural Repeats Using a Chain Graph Model |

Yan Liu, Eric Xing, Jaime Carbonell |

Unsupervised Evidence Integration |

Philip M. Long, Vinay Varadan, Sarah Gilman, Mark Treshock, Rocco A. Servedio |

Naive Bayes Models for Probability Estimation |

Daniel Lowd, Pedro Domingos |

ROC Confidence Bands : An Empirical Evaluation |

Sofus A. Macskassy, Foster Provost, Saharon Rosset |

Modeling Word Burstiness Using the Dirichlet Distribution |

Rasmus Madsen, David Kauchak, Charles Elkan |

Proto-Value Functions: Developmental Reinforcement Learning |

Sridhar Mahadeva |

The cross entropy method for classification |

Shie Mannor, Dori Peleg, Reuven Y. Rubinstein |

Bounded Real-Time Dynamic Programming: RTDP with monotone upper bounds and performance guarantees |

H. Brendan McMahan, Maxim Likhachev, Geoffrey J. Gordon |

Comparing Clusterings - An Axiomatic View |

Marina Meila |

Weighted Decomposition Kernels |

Sauro Menchetti, Fabrizio Costa, Paolo Frasconi |

High Speed Obstacle Avoidance using Monocular Vision and Reinforcement learning |

Jeff Michels, Ashutosh Saxena, Andrew Y. Ng |

Dynamic Preferences in Multi-Criteria Reinforcement Learning |

Sriraam Natarajan, Prasad Tadepalli |

Learning First-Order Probabilistic Models with Combining Rules |

Sriraam Natarajan, Prasad Tadepalli, Eric Altendorf, Thomas G. Dietterich, Alan Fern, Angelo Restificar |

An Efficient Method for Simplifying Support Vector Machines |

DucDung Nguyen, Tu Bao Ho |

Predicting Good Probabilities With Supervised Learning |

Alexandru Niculescu-Mizil, Rich Caruana |

Recycling Data for Multi-Agent Learning |

Santiago Ontañon, Enric Plaza |

A Graphical Model for Chord Progressions Embedded in a Psychoacoustic Space |

Jean-François Paiement, Douglas Eck, Samy Bengio, David Barber |

Q-Learning of Sequential Attention for Visual Object Recognition from Informative Local Descriptors |

Lucas Paletta, Gerald Fritz, Christin Seifert |

Discriminative versus Generative Parameter and Structure Learning of Bayesian Network Classifiers |

Franz Pernkopf, Jeff Bilmes |

Optimizing Abstaining Classifiers using ROC Analysis |

Tadeusz Pietraszek |

Independent Subspace Analysis Using Geodesic Spanning Trees |

Barnabas Poczos, András Lörincz |

A Model for Handling Approximate, Noisy or Incomplete Labeling in Text Classification |

Ganesh Ramakrishnan, Krishna Prasad Chitrapura, Raghu Krishnapuram, Pushpak Bhattacharyya |

Healing the Relevance Vector Machine through Augmentation |

Carl Edward Rasmussen, Joaquin Quinonero-Candela |

Supervised versus Multiple Instance Learning: An Empirical Comparison |

Soumya Ray, Mark Craven |

Generalized Skewing for Functions with Continuous and Nominal Attributes |

Soumya Ray, David Page |

Fast Maximum Margin Matrix Factorization for Collaborative Prediction |

Jason D. M. Rennie, Nati Srebro |

Coarticulation: An Approach for Generating Concurrent Plans in Markov Decision Processes |

Khashayar Rohanimanesh, Sridhar Mahadevan |

Why Skewing Works: Learning Difficult Boolean Functions with Greedy Tree Learners |

Bernard Rosell, Lisa Hellerstein, Soumya Ray, David Page |

Integer Linear Programming Inference for Conditional Random Fields |

Dan Roth, Wen-Tau Yih |

Learning Hierarchical Multi-Category Text Classification Models |

Juho Rousu, Craig Saunders, Sandor Szedmak, John Shawe-Taylor |

Expectation Maximization Algorithms for Conditional Likelihoods |

Jarkko Salojärvi, Kai Puolamäki, Samuel Kaski |

Estimating and computing density based distance metrics |

Sajama, Alon Orlitsky |

Supervised dimensionality reduction using mixture models |

Sajama, Alon Orlitsky |

Object Correspondence as a Machine Learning Problem |

Bernhard Schölkopf, Florian Steinke, Volker Blanz |

Analysis and Extension of Spectral Methods for Nonlinear Dimensionality Reduction |

Fei Sha, Lawrence K. Saul |

Non-Negative Tensor Factorization with Applications to Statistics and Computer Vision |

Amnon Shashua, Tamir Hazan |

Fast Inference and Learning in Large-State-Space HMMs |

Sajid M. Siddiqi, Andrew W. Moore |

New D-Separation Identification Results for Learning Continuous Latent Variable Models |

Ricardo Silva, Richard Scheines |

Identifying Useful Subgoals in Reinforcement Learning by Local Graph Partitioning |

Ozgur Simsek, Alicia Wolfe, Andrew Barto |

Beyond the Point Cloud: from Transductive to Semi-supervised Learning |

Vikas Sindhwani, Partha Niyogi, Mikhail Belkin |

Active Learning for Sampling in Time-Series Experiments With Application to Gene Expression Analysis |

Rohit Singh, Nathan Palmer, David Gifford, Bonnie Berger, Ziv Bar-Joseph |

Compact approximations to Bayesian predictive distributions |

Edward Snelson, Zoubin Ghahramani |

Large Scale Genomic Sequence SVM Classifiers |

Sören Sonnenburg, Gunnar Rätsch, Bernhard Schölkopf |

A Theoretical Analysis of Model-Based Interval Estimation |

Alexander L. Strehl, Michael L. Littman |

Explanation-Augmented SVM: an Approach to Incorporating Domain Knowledge into SVM Learning |

Qiang Sun, Gerald DeJong |

Unifying the Error-Correcting and Output-Code AdaBoost within the Margin Framework |

Yijun Sun, Sinisa Todorovic, Jian Li, Dapeng Wu |

Finite Time Bounds for Sampling Based Fitted Value Iteration |

Csaba Szepesvári, Rémi Munos |

TDLambda Networks: Temporal-Difference Networks with Eligibility Traces |

Brian Tanner, Richard Sutton |

Learning Structured Prediction Models: A Large Margin Approach |

Ben Taskar, Vassil Chatalbashev, Daphne Koller, Carlos Guestrin |

Learning Discontinuities with Products-of-Sigmoids for Switching between Local Models |

Marc Toussaint, Sethu Vijayakumar |

Core Vector Regression for Very Large Regression Problems |

Ivor W. Tsang, James T. Kwok, Kimo T. Lai |

Propagating Distributions on a Hypergraph by Dual Information Regularization |

Koji Tsuda |

Hierarchical Dirichlet Model for Document Classification |

Sriharsha Veeramachaneni, Diego Sona, Paolo Avesani |

Implicit Surface Modelling as an Eigenvalue Problem |

Christian Walder, Olivier Chapelle, Bernhard Schölkopf |

New Kernels for Protein Structural Motif Discovery and Function Classification |

Chang Wang, Stephen Scott |

Exploiting Syntactic, Semantic and Lexical Regularities in Language Modeling via Directed Markov Random Fields |

Shaojun Wang, Shaomin Wang, Russell Greiner, Dale Schuurmans, Li Cheng |

Bayesian Sparse Sampling for On-line Reward Optimization |

Tao Wang, Daniel J. Lizotte, Michael Bowling, Dale Schuurmans |

Learning Predictive Representations from a History |

Eric Wiewiora |

Incomplete-Data Classification using Logistic Regression |

David Williams, Xuejun Liao, Ya Xue, Lawrence Carin |

Learning Predictive State Representations in Dynamical Systems Without Reset |

Britton Wolfe, Michael R. James, Satinder Singh |

Linear Asymmetric Classifier for Cascade Detectors |

Jianxin Wu, Matthew D. Mullin, James M. Rehg |

Building Sparse Large Margin Classifiers |

Mingrui Wu, Bernhard Schölkopf, Goekhan Bakir |

Dirichlet Enhanced Relational Learning |

Zhao Xu, Volker Tresp, Kai Yu, Shipeng Yu, Hans-Peter Kriegel |

Learning Gaussian Processes from Multiple Tasks |

Kai Yu, Volker Tresp, Anton Schwaighofer |

Augmenting Naive Bayes for Ranking |

Harry Zhang, Liangxiao Jiang, Jiang Su |

A New Mallows Distance Based Metric For Comparing Clusterings |

Ding Zhou, Jia Li, Hongyuan Zha |

Learning from Labeled and Unlabeled Data on a Directed Graph |

Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf |

2D Conditional Random Fields for Web Information Extraction |

Jun Zhu, Zaiqing Nie, Ji-Rong Wen, Bo Zhang, Wei-Ying Ma |

Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning |

Xiaojin Zhu, John Lafferty |

Large Margin Non-Linear Embedding |

Alexander Zien, Joaquin Quinonero-Candela |