The International Machine Learning Society
ICML 2007
- The Twenty-Fourth International Conference on Machine Learning
- was held June 20-24, 2007, Oregon State University, Corvallis, USA. Proceedings of the conference can be purchased from Omnipress
ICML 2007 Proceedings
Please refer to papers in this volume as:
Zoubin Ghahramani (Ed.) Proceedings of the 24th International Conference on Machine Learning, Omni Press, 2007 [All accepted papers (58MB)] [Citations (BibTex)]
Quantum Clustering Algorithms
Esma Ämeur - Université de Montréal, Canada
Gilles Brassard - Université de Montréal, Canada
Sébastien Gambs - Université de Montréal, Canada
Learning Random Walks to Rank Nodes in Graphs
Alekh Agarwal - IIT Bombay, India
Soumen Chakrabarti - IIT Bombay, India
Two-view Feature Generation Model for Semi-supervised Learning
Rie Ando - IBM T.J. Watson Research Center, USA
Tong Zhang - Yahoo Inc., USA
Scalable Training of L1-regularized Log-linear Models
Galen Andrew - Microsoft Research, USA
Jianfeng Gao - Microsoft Research, USA
Multiclass Core Vector Machine
- Asharaf - Computer Science and Automation, Indian Institute of Science, Bangalore - 560012, India
- Narasimha Murty - Computer Science and Automation, Indian Institute of Science, Bangalore - 560012, India
- Shevade - Computer Science and Automation, Indian Institute of Science, Bangalore - 560012, India
The Rendezvous Algorithm: Multiclass Semi-Supervised Learning with Markov Random Walks
Arik Azran - University of Cambridge, UK
Focussed Crawling with Scalable Ordinal Regression Solvers
Rashmin Babaria - Indian Institute of Science, INDIA
Saketha Nath Jagarlapudi - Indian Institute of Science, INDIA
Krishnan S. Kumar - Indian Institute of Science, INDIA
Sivaramakrishnan Ramanujam Kaveri - Indian Institute of Science, INDIA
Chiranjib Bhattacharyya - Indian Institute of Science, INDIA
- Narasimha Murty - Indian Institute of Science, INDIA
Learning Distance Function by Coding Similarity
Aharon Bar Hillel - Intel research, Israel
Daphna Weinshall - The Hebrew university of Jerusalem, Israel
Structural Alignment based Kernels for Protein Structure Classification
Sourangshu Bhattacharya - Indian Institute of Science, India
Chiranjib Bhattacharyya - Indian Institute of Science, India
Nagasuma R. Chandra - Indian Institute of Science, India
Discriminative Learning for Differing Training and Test Distributions
Steffen Bickel - Max Planck Institute for Computer Science, Germany
Michael Brüeckner - Max Planck Institute for Computer Science, Germany
Tobias Scheffer - Max Planck Institute for Computer Science, Germany
Solving MultiClass Support Vector Machines with LaRank
Antoine Bordes - LIP, Universite de Paris 6,104 Avenue du Pdt Kennedy, 75016 Paris, France
Léon Bottou - NEC Laboratories America, Inc.,, USA
Patrick Gallinari - LIP, Universite de Paris 6,104 Avenue du Pdt Kennedy, 75016 Paris, France
Jason Weston - NEC Laboratories America, Inc.,, USA
Efficiently Computing Minimax Expected-Size Confidence Regions
Brent Bryan - Machine Learning Department; Carnegie Mellon University, USA
- Brendan McMahan - Google Pittsburgh, USA
Chad M. Schafer - Department of Statistics; Carnegie Mellon University, USA
Jeff Schneider - Robotics Institute; Carnegie Mellon University, USA
Multiple Instance Learning for Sparse Positive Bags
Razvan C. Bunescu - University of Texas at Austin, USA
Raymond J. Mooney - University of Texas at Austin, USA
Cluster Analysis of Heterogeneous Rank Data
Ludwig M. Busse - Institute of Computational Science, ETH Zurich, Switzerland
Peter Orbanz - Institute of Computational Science, ETH Zurich, Switzerland
Joachim M. Buhmann - Institute of Computational Science, ETH Zurich, Switzerland
Feature Selection in Kernel Space
Bin Cao - Peking University, China
Dou Shen - Hong Kong University of Science and Technology, China
Jian-Tao Sun - Microsoft Research Asia, China
Qiang Yang - Hong Kong University of Science and Technology, China
Zheng Chen - Microsoft Research Asia, China
Learning to Rank: From Pairwise Approach to Listwise Approach
Zhe Cao - Tsinghua University, China
Tao Qin - Tsinghua University, China
Tie-Yan Liu - Microsoft Research Asia, China
Ming-Feng Tsai - National Taiwan University, China
Hang Li - Microsoft Research Asia, China
Local Similarity Discriminant Analysis
Luca Cazzanti - Applied Physics Lab-University of Washington, USA
Maya Gupta - University of Washington, USA
Direct Convex Relaxations of Sparse SVM
Antoni B. Chan - University of California, San Diego, USA
Nuno Vasconcelos - University of California, San Diego, USA
Gert R. G. Lanckriet - University of California, San Diego, USA
Minimum Reference Set Based Feature Selection for Small Sample Classifications
Xue-wen Chen - Department of Electrical Engineering and Computer Science, The University of Kansas, USA
Jong Cheol Jeong - Department of Electrical Engineering and Computer Science, The University of Kansas, USA
Learning to Compress Images and Video
Li Cheng - National ICT Australia, Australia
S.V.N. Vishwanathan - National ICT Australia, Australia
Magnitude-Preserving Ranking Algorithms
Corinna Cortes - Google Research, New York, USA
Mehryar Mohri - Courant Institute of Mathematical Sciences and Google Research, USA
Ashish Rastogi - Courant Institute of Mathematical Sciences, New York University, USA
Full Regularization Path for Sparse Principal Component Analysis
Alexandre d’Aspremont - Princeton University, USA
Francis R. Bach - Ecole des Mines de Paris, France
Laurent El Ghaoui - U.C. Berkeley, USA
Kernel Selection for Semi-Supervised Kernel Machines
Guang Dai - Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong
Dit-Yan Yeung - Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong
Boosting for Transfer Learning
Wenyuan Dai - Shanghai Jiao Tong University, China
Qiang Yang - Hong Kong University of Science and Technology, Hong Kong, China
Gui-Rong Xue - Shanghai Jiao Tong University, China
Yong Yu - Shanghai Jiao Tong University, China
Intractability and Clustering with Constraints
Ian Davidson - SUNY - Albany, USA
S.S. Ravi - SUNY - Albany, USA
Information-Theoretic Metric Learning
Jason V. Davis - University of Texas at Austin, USA
Brian Kulis - University of Texas at Austin, USA
Prateek Jain - University of Texas at Austin, USA
Suvrit Sra - University of Texas at Austin, USA
Inderjit S. Dhillon - University of Texas at Austin, USA
An Integrated Approach to Feature Invention and Model Construction for Drug Activity Prediction
Jesse Davis - University of Wisconsin-Madison, USA
Vítor Santos Costa - University of Porto, Portugal
Soumya Ray - Oregon State University, USA
David Page - University of Wisconsin-Madison, USA
Percentile Optimization in Uncertain MDP with Application to Efficient Exploration
Erick Delage - Stanford University, USA
Shie Mannor - McGill University, Canada
Unsupervised Prediction of Citation Influences
Laura Dietz - Max Planck Institute for Computer Science, Germany
Steffen Bickel - Max Planck Institute for Computer Science, Germany
Tobias Scheffer - Max Planck Institute for Computer Science, Germany
Non-Isometric Manifold Learning: Analysis and an Algorithm
Piotr Dollár - University Of California, San Diego, United States
Vincent Rabaud - University Of California, San Diego, United States
Serge Belongie - University Of California, San Diego, United States
Hierarchical Maximum Entropy Density Estimation
Miroslav Dudík - Princeton University, U.S.
David M. Blei - Princeton University, U.S.
Robert E. Schapire - Princeton University, U.S.
CarpeDiem: an Algorithm for the Fast Evaluation of SSL Classifiers
Roberto Esposito - Università di Torino, Italy
Daniele P. Radicioni - Università di Torino, Italy
Manifold-adaptive dimension estimation
Amir massoud Farahmand - University of Alberta, Canada
Csaba Szepesvári - University of Alberta, Canada
Jean-Yves Audibert - Certis - Ecole des Ponts - ParisTech, France
Combining Online and Offline Knowledge in UCT
Sylvain Gelly - Univ. Paris Sud, LRI, CNRS, INRIA, France
David Silver - University of Alberta, Canada
Robust Non-linear Dimensionality Reduction using Successive 1-Dimensional Laplacian Eigenmaps
Samuel Gerber - University of Utah, US
Tolga Tasdizen - University of Utah, US
Ross Whitaker - University of Utah, US
Gradient Boosting for Kernelized Output Spaces
Pierre Geurts - University of Liège, Belgium
Louis Wehenkel - University of Liège, Belgium
Florence d’Alché-Buc - University of Evry, France
Bayesian Actor-Critic Algorithms
Mohammad Ghavamzadeh - University of Alberta, Canada
Yaakov Engel - University of Alberta, Canada
Exponentiated Gradient Algorithms for Log-Linear Structured Prediction
Amir Globerson - MIT, USA
Terry Koo - MIT, USA
Xavier Carreras - MIT, USA
Michael Collins - MIT, USA
Best of Both: A Hybridized Centroid-Medoid Clustering Heuristic
Nizar Grira - National Institute of Informatics, Japan
Michael E. Houle - National Institute of Informatics, Japan
Recovering Temporally Rewiring Networks: A model-based approach
Fan Guo - Carnegie Mellon University, USA
Steve Hanneke - Carnegie Mellon University, USA
Wenjie Fu - Carnegie Mellon University, USA
Eric P. Xing - Carnegie Mellon University, USA
Efficient Inference with Cardinality-based Clique Potentials
Rahul Gupta - IBM Research Lab, New Delhi, India
Ajit A. Diwan - IIT Bombay, India
Sunita Sarawagi - IIT Bombay, India
Sparse Probabilistic Classifiers
Romain Hérault - Heudiasyc UMR 6599 Universite de Technologie de Compiegne, France
Yves Grandvalet - Heudiasyc UMR 6599 Universite de Technologie de Compiegne, France
Supervised Clustering of Streaming Data for Email Batch Detection
Peter Haider - Max Planck Institute for Computer Science, Germany
Ulf Brefeld - Max Planck Institute for Computer Science, Germany
Tobias Scheffer - Max Planck Institute for Computer Science, Germany
A Bound on the Label Complexity of Agnostic Active Learning
Steve Hanneke - Carnegie Mellon University, USA
Learning Nonparametric Kernel Matrices from Pairwise Constraints
Steven C. H. Hoi - The Chinese University of Hong Kong, China
Rong Jin - Michigan State University, USA
Michael R. Lyu - The Chinese University of Hong Kong, China
Parameter Learning for Relational Bayesian Networks
Manfred Jaeger - Aalborg University, Denmark
Bayesian Compressive Sensing and Projection Optimization
Shihao Ji - Duke University, USA
Lawrence Carin - Duke University, USA
Constructing Basis Functions from Directed Graphs for Value Function Approximation
Jeffrey Johns - University of Massachusetts Amherst, U.S.A.
Sridhar Mahadevan - University of Massachusetts Amherst, U.S.A.
Most Likely Heteroscedastic Gaussian Process Regression
Kristian Kersting - MIT CSAIL, USA
Christian Plagemann - University of Freiburg, Germany
Patrick Pfaff - University of Freiburg, Germany
Wolfram Burgard - University of Freiburg, Germany
Neighbor Search with Global Geometry: A Minimax Message Passing Algorithm
Kye-Hyeon Kim - Pohang University of Science and Technology, Korea
Seungjin Choi - Pohang University of Science and Technology, Korea
A Recursive Method for Discriminative Mixture Learning
Minyoung Kim - Rutgers University, USA
Vladimir Pavlovic - Rutgers University, USA
Infinite Mixtures of Trees
Sergey Kirshner - University of Alberta, Canada
Padhraic Smyth - University of California, Irvine, USA
Local Dependent Components
Arto Klami - Helsinki University of Technology, Finland
Samuel Kaski - Helsinki University of Technology, Finland
Statistical Predicate Invention
Stanley Kok - University of Washington, USA
Pedro Domingos - University of Washington, USA
Kernelizing PLS, Degrees of Freedom, and Efficient Model Selection
Nicole Krämer - TU Berlin, Germany
Mikio L. Braun - TU Berlin, Germany
Nonmyopic Active Learning of Gaussian Processes: An Exploration—Exploitation Approach
Andreas Krause - Carnegie Mellon University, USA
Carlos Guestrin - Carnegie Mellon University, USA
On One Method of Non-Diagonal Regularization in Sparse Bayesian Learning
Dmitry Kropotov - Dorodnicyn Computing Centre of the Russian Academy of Sciences, Russia
Dmitry Vetrov - Dorodnicyn Computing Centre of the Russian Academy of Sciences, Russia
Online Kernel PCA with Entropic Matrix Updates
Dima Kuzmin - University of California - Santa Cruz, USA
Manfred K. Warmuth - University of California - Santa Cruz, USA
An Empirical Evaluation of Deep Architectures on Problems with Many Factors of Variation
Hugo Larochelle - Université de Montréal, Canada
Dumitru Erhan - Université de Montréal, Canada
Aaron Courville - Université de Montréal, Canada
James Bergstra - Université de Montréal, Canada
Yoshua Bengio - Université de Montréal, Canada
The Hierarchical Gaussian Process Latent Variable Model
Neil D. Lawrence - School of Computer Science, University of Manchester, U.K.
Andrew J. Moore - Department of Computer Science, University of Sheffield, U.K.
Scalable Modeling of Real Graphs using Kronecker Multiplication
Jure Leskovec - Carnegie Mellon University, USA
Christos Faloutsos - Carnegie Mellon University, USA
Support Cluster Machine
Bin Li - Department of Computer Science and Engineering, Fudan University, P. R. China
Mingmin Chi - Department of Computer Science and Engineering, Fudan University, P. R. China
Jianping Fan - Department of Computer Science, University of North Carolina, Charlotte., USA
Xiangyang Xue - Department of Computer Science and Engineering, Fudan University, P. R. China
A Transductive Framework of Distance Metric Learning by Spectral Dimensionality Reduction
Fuxin Li - Institute of Automation, Chinese Academy of Sciences, China
Jian Yang - Beijing University of Technology, China
Jue Wang - Institute of Automation, Chinese Academy of Sciences, China
Adaptive Dimension Reduction Using Discriminant Analysis and $K$-means Clustering
Tao Li - Florida International University, USA
Chris Ding - Lawrence Berkeley National Lab, USA
Large-scale RLSC Learning Without Agony
Wenye Li - Dept. Computer Science and Engineering, the Chinese University of Hong Kong, China
Kin-Hong Lee - Dept. Computer Science and Engineering, the Chinese University of Hong Kong, China
Kwong-Sak Leung - Dept. Computer Science and Engineering, the Chinese University of Hong Kong, China
A Novel Orthogonal NMF-Based Belief Compression for POMDPs
Xin Li - Computer Science Department, Hong Kong Baptist University, Hong Kong, China
William K. W. Cheung - Computer Science Department, Hong Kong Baptist University, Hong Kong, China
Jiming Liu - Computer Science Department, Hong Kong Baptist University, Hong Kong, China
Zhili Wu - Computer Science Department, Hong Kong Baptist University, Hong Kong, China
A Permutation-augmented Sampler for DP Mixture Models
Percy Liang - UC Berkeley, USA
Michael I. Jordan - UC Berkeley, USA
Ben Taskar - University of Pennsylvania, USA
Quadratically Gated Mixture of Experts for Incomplete Data Classification
Xuejun Liao - Duke University, USA
Hui Li - Duke University, USA
Lawrence Carin - Duke University, USA
Trust Region Newton Methods for Large-Scale Logistic Regression
Chih-Jen Lin - National Taiwan University, Taiwan
Ruby Chiu-Hsing Weng - National Chengche University, Taiwan
Sathiya Keerthi - Yahoo Research, USA
Relational Clustering by Symmetric Convex Coding
Bo Long - SUNY at Binghamton, USA
Zhongfei Zhang - SUNY at Binghamton, USA
Xiaoyun Wu - Google Inc., USA
Philip S. Yu - IBM Watson Reasearch center, USA
Discriminant Analysis in Correlation Similarity Measure Space
Yong Ma - Sensing & Control Lab., Omron Corporation, Japan
Shihong Lao - Sensing & Control Lab., Omron Corporation, Japan
Erina Takikawa - Sensing & Control Lab., Omron Corporation, Japan
Masato Kawade - Sensing & Control Lab., Omron Corporation, Japan
Adaptive Mesh Compression in 3D Computer Graphics using Multiscale Manifold Learning
Sridhar Mahadevan - University of Massachusetts, Amherst, USA
Simple, Robust, Scalable Semi-supervised Learning via Expectation Regularization
Gideon S. Mann - University of Massachusetts, USA
Andrew McCallum - University of Massachusetts, USA
Automatic Shaping and Decomposition of Reward Functions
Bhaskara Marthi - Massachusetts Institute of Technology, USA
Asymmetric Boosting
Hamed Masnadi-Shirazi - UCSD, USA
Nuno Vasconcelos - UCSD, USA
Linear and Nonlinear Generative Probabilistic Class Models for Shape Contours
Graham McNeill - University of Edinburgh, UK
Sethu Vijayakumar - University of Edinburgh, UK
Bottom-Up Learning of Markov Logic Network Structure
Lilyana Mihalkova - The University of Texas at Austin, USA
Raymond J. Mooney - The University of Texas at Austin, USA
Mixtures of Hierarchical Topics with Pachinko Allocation
David Mimno - University of Massachusetts, Amherst, USA
Wei Li - University of Massachusetts, Amherst, USA
Andrew McCallum - University of Massachusetts, Amherst, USA
Three New Graphical Models for Statistical Language Modelling
Andriy Mnih - University of Toronto, Canada
Geoffrey Hinton - University of Toronto, Canada
Fast and Effective Kernels for Relational Learning from Texts
Alessandro Moschitti - University of Trento, Italy
Fabio Massimo Zanzotto - University of Rome, Italy
Dimensionality Reduction and Generalization
Sofia Mosci - DIFI & DISI, Universita’ di Genova, Italy
Lorenzo Rosasco - DISI, Universita’ di Genova, Italy
Alessandro Verri - DISI, Universita’ di Genova, Italy
Unsupervised Estimation for Noisy-Channel Models
Markos Mylonakis - University of Amsterdam, The Netherlands
Khalil Sima’an - University of Amsterdam, The Netherlands
Rebecca Hwa - University of Pittsburgh, USA
Revisiting Probabilistic Models for Clustering with Constraints
Blaine Nelson - University of California, Berkeley, USA
Ira Cohen - Hewlett-Packard Research Labs, USA
Comparisons of Sequence Labeling Algorithms and Extensions
Nam Nguyen - Department of Computer Science, Cornell University, USA
Yunsong Guo - Department of Computer Science, Cornell University, USA
Multi-Task Learning for Sequential Data via iHMMs and the Nested Dirichlet Process
Kai Ni - Duke University, USA
Lawrence Carin - Duke University, USA
David Dunson - Duke University, USA
Regression on Manifolds using Kernel Dimension Reduction
Jens Nilsson - Centre for Mathematical Sciences, Lund University, Sweden
Fei Sha - Computer Science Division, University of California, Berkeley, USA
Michael I. Jordan - Computer Science Division and Department of Statistics, University of California, Berkeley, USA
Learning State-Action Basis Functions for Hierarchical MDPs
Sarah Osentoski - University of Massachusetts Amherst, USA
Sridhar Mahadevan - University of Massachusetts Amherst, USA
A Fast Linear Separability Test by Projection of Positive Points on Subspaces
Yogananda A. P. - Satyam Computer Services Ltd., India
- Narasimha Murty - Indian Institute of Science, India
Lakshmi Gopal - Satyam Computer Services Ltd., India
Multi-armed Bandit Problems with Dependent Arms
Sandeep Pandey - Yahoo, USA
Deepayan Chakrabarti - Yahoo, USA
Deepak Agarwal - Yahoo, USA
Learning for Efficient Retrieval of Structured Data with Noisy Queries
Charles Parker - Oregon State University, United States
Alan Fern - Oregon State University, United States
Prasad Tadepalli - Oregon State University, United States
Analyzing Feature Generation for Value-Function Approximation
Ronald Parr - Duke University, USA
Christopher Painter-Wakefield - Duke University, USA
Lihong Li - Rutgers University, USA
Michael Littman - Rutgers University, USA
Reinforcement Learning by Reward-weighted Regression for Operational Space Control
Jan Peters - Max Planck Institute for Biological Cybernetics, Germany
Stefan Schaal - University of Southern California, USA
Tracking Value Function Dynamics to Improve Reinforcement Learning with Piecewise Linear Function Approximation
Chee Wee Phua - National ICT Australia, Australia
Robert Fitch - National ICT Australia, Australia
Self-taught Learning: Transfer Learning from Unlabeled Data
Rajat Raina - Stanford University, USA
Alexis Battle - Stanford University, USA
Honglak Lee - Stanford University, USA
Benjamin Packer - Stanford University, USA
Andrew Y. Ng - Stanford University, USA
Online Discovery of Similarity Mappings
Alexander Rakhlin - UC Berkeley, USA
Jacob Abernethy - UC Berkeley, USA
Peter L. Bartlett - UC Berkeley, USA
More Efficiency in Multiple Kernel Learning
Alain Rakotomamonjy - Lab ITIS EA4051, Université de Rouen, France
Francis R. Bach - CMM, Ecole des Mines de Paris, France
Stephane Canu - Lab ITIS EA4051, INSA de Rouen, France
Yves Grandvalet - IDIAP, Switzerland
Graph Clustering With Network Structure Indices
Matthew J. Rattigan - University of Massachusetts Amherst, USA
Marc Maier - University of Massachusetts Amherst, USA
David Jensen - University of Massachusetts Amherst, USA
Restricted Boltzmann Machines for Collaborative Filtering
Ruslan Salakhutdinov - University of Toronto, Canada
Andriy Mnih - University of Toronto, Canada
Geoffrey Hinton - University of Toronto, Canada
Sample Compression Bounds for Decision Trees
Mohak Shah - CHUL Research Centre, Faculty of Medicine, Laval University, Canada
Pegasos: Primal Estimated sub-GrAdient SOlver for SVM
Shai Shalev-Shwartz - Hebrew University, Israel
Yoram Singer - Google Inc., USA
Nathan Srebro - Toyota Technological Institute at Chicago, USA
A Dependence Maximization View of Clustering
Le Song - National ICT Australia, Australia
Alex Smola - National ICT Australia, Australia
Arthur Gretton - MPI Tübingen, Germany
Karsten M. Borgwardt - LMU München, Germany
Supervised Feature Selection via Dependence Estimation
Le Song - National ICT Australia, Australia
Alex Smola - National ICT Australia, Australia
Arthur Gretton - MPI Tübingen, Germany
Karsten M. Borgwardt - LMU München, Germany
Justin Bedo - National ICT Australia, Australia
Sparse Eigen Methods by D.C. Programming
Bharath Sriperumbudur - University of California, San Diego, USA
David Torres - University of California, San Diego, USA
Gert Lanckriet - University of California, San Diego, USA
Learning to Solve Game Trees
David Stern - University of Cambridge, UK
Ralf Herbrich - Microsoft Research Ltd., UK
Thore Graepel - Microsoft Research Ltd., UK
Robust Mixtures in the Presence of Measurement Errors
Jianyong Sun - School of Computer Science and School of Physics and Astronomy, University of Birmingham, United Kingdom
Ata Kaban - School of Computer Science, University of Birmingham, United Kingdom
Somak Raychaudhury - School of Physics and Astronomy, University of Birmingham, United Kingdom
A Kernel-based Causal Learning Algorithm
Xiaohai Sun - Max Planck Institute for Biological Cybernetics, Germany
Dominik Janzing - Universitaet Karlsruhe (TH), Germany
Bernhard Schölkopf - Max Planck Institute for Biological Cybernetics, Germany
Kenji Fukumizu - Institute of Statistical Mathematics, 4-6-7 Minami-Azabu, Minato-ku, Tokyo 106-8569, Japan
Piecewise Pseudolikelihood for Efficient Training of Conditional Random Fields
Charles Sutton - University of Massachusetts, United States
Andrew McCallum - University of Massachusetts, United States
On the Role of Tracking in Stationary Environments
Richard S. Sutton - University of Alberta, Canada
Anna Koop - University of Alberta, Canada
David Silver - University of Alberta, Canada
Cross-Domain Transfer for Reinforcement Learning
Matthew E. Taylor - The University of Texas at Austin, USA
Peter Stone - The University of Texas at Austin, USA
Incremental Bayesian Networks for Structure Prediction
Ivan Titov - University of Geneva, Switzerland
James Henderson - University of Edinburgh, United Kingdom
Classifying Matrices with a Spectral Regularization
Ryota Tomioka - Dept. of Mathematical Informatics, IST, The University of Tokyo, Japan
Kazuyuki Aihara - Institute of Industrial Science, The University of Tokyo, Japan
Approximate Maximum Margin Algorithms with Rules Controlled by the Number of Mistakes
Petroula Tsampouka - University of Southampton, UK
John Shawe-Taylor - University College London, UK
Simpler Core Vector Machines with Enclosing Balls
Ivor W. Tsang - Hong Kong University of Science and Technology, Hong Kong
Andras Kocsor - University of Szeged, Hungary
James T. Kwok - Hong Kong University of Science and Technology, Hong Kong
Entire Regularization Paths for Graph Data
Koji Tsuda - Max Planck Institute for Biological Cybernetics, Germany
Discriminative Gaussian Process Latent Variable Models for Classification
Raquel Urtasun - Computer Science and Artificial Intelligence Laboratory, MIT, USA
Trevor Darrell - Computer Science and Artificial Intelligence Laboratory, MIT, USA
Experimental Perspectives on Learning from Imbalanced Data
Jason D. Van Hulse - Florida Atlantic University, USA
Taghi M. Khoshgoftaar - Florida Atlantic University, USA
Amri Napolitano - Florida Atlantic University, USA
Learning from Interpretations: A Rooted Kernel for Ordered Hypergraphs
Gabriel Wachman - Tufts University, USA
Roni Khardon - Tufts University, USA
A Kernel Path Algorithm for Support Vector Machines
Gang Wang - Hong Kong University of Science and Technology, China
Dit-Yan Yeung - Hong Kong University of Science and Technology, China
Frederick Lochovsky - Hong Kong University of Science and Technology, China
Dirichlet Aggregation: Unsupervised Learning towards an Optimal Metric for Proportional Data
Hua-Yan Wang - State Key Laboratory of Machine Perception, Peking University, China
Hongbin Zha - State Key Laboratory of Machine Perception, Peking University, China
Hong Qin - Department of Computer Science, State University of New York at Stony Brook, USA
Transductive Regression Piloted by Inter-Manifold Relations
Huan Wang - The Chinese University of Hong Kong, China
Shuicheng Yan - University of Illinois at Urbana-Champaign, USA
Thomas Huang - University of Illinois at Urbana-Champaign, USA
Jianzhuang Liu - The Chinese University of Hong Kong, China
Xiaoou Tang - The Chinese University of Hong Kong, China
Multifactor Gaussian Process Models for Style-Content Separation
Jack M. Wang - University of Toronto, Canada
David J. Fleet - University of Toronto, Canada
Aaron Hertzmann - University of Toronto, Canada
Hybrid Huberized Support Vector Machines for Microarray Classification
Li Wang - Ross School of Business, University of Michigan, U.S.
Ji Zhu - Department of Statistics, University of Michigan, U.S.
Hui Zou - School of Statistics, University of Minnesota, U.S.
On Learning with Dissimilarity Functions
Liwei Wang - Peking University, China
Cheng Yang - Peking University, China
Jufu Feng - Peking University, China
Winnowing Subspaces
Manfred K. Warmuth - University of California at Santa Cruz, USA
What Is Decreased by the Max-sum Arc Consistency Algorithm?
Tomáš Werner - Dept. of Cybernetics, Faculty of Electrical Engineering, Czech Technical University, Prague, Czech Republic
Multi-Task Reinforcement Learning: A Hierarchical Bayesian Approach
Aaron Wilson - Oregon State University, USA
Alan Fern - Oregon State University, USA
Prasad Tadepalli - Oregon State University, USA
Soumya Ray - Oregon State University, USA
Beamforming using the Relevance Vector Machine
David Wipf - University of California, San Francisco, USA
Srikantan Nagarajan - University of California, San Francisco, USA
Learning to Combine Distances for Complex Representations
Adam Woznica - University of Geneva, Switzerland
Alexandros Kalousis - University of Geneva, Switzerland
Melanie Hilario - University of Geneva, Switzerland
Local Learning Projections
Mingrui Wu - Max Planck Institute for Biological Cybernetics, Germany
Kai Yu - NEC Labs America, USA
Shipeng Yu - Siemens Medical Solutions, USA
Bernhard Schölkopf - Max Planck Institute for Biological Cybernetics, Germany
On Learning Linear Ranking Functions for Beam Search
Yuehua Xu - School of EECS, Oregon State University, USA
Alan Fern - School of EECS, Oregon State University, USA
Modeling Changing Dependency Structure in Multivariate Time Series
Xiang Xuan - UBC, Canada
Kevin Murphy - UBC, Canada
The Matrix Stick-Breaking Process for Flexible Multi-Task Learning
Ya Xue - Department of Electrical & Computer Engineering, Duke University, USA
David Dunson - Biostatistics Branch, National Institute of Environmental Health Sciences, USA
Lawrence Carin - Department of Electrical & Computer Engineering, Duke University, USA
Map Building without Localization by Dimensionality Reduction Techniques
Takehisa Yairi - University of Tokyo, Japan
Asymptotic Bayesian Generalization Error When Training and Test Distributions Are Different
Keisuke Yamazaki - Tokyo Institute of Technology, Japan
Motoaki Kawanabe - Fraunhofer FIRST IDA, Germany
Sumio Watanabe - Tokyo Institute of Technology, Japan
Masashi Sugiyama - Tokyo Institute of Technology, Japan
Klaus-Robert Müller - Fraunhofer FIRST IDA, Technical University of Berlin, Germany
Least Squares Linear Discriminant Analysis
Jieping Ye - Department of Computer Science and Engineering, Arizona State University, USA
Discriminant Kernel and Regularization Parameter Learning via Semidefinite Programming
Jieping Ye - Department of Computer Science and Engineering, Arizona State University, USA
Jianhui Chen - Department of Computer Science and Engineering, Arizona State University, USA
Shuiwang Ji - Department of Computer Science and Engineering, Arizona State University, USA
Robust Multi-Task Learning with $t$-Processes
Shipeng Yu - CAD and Knowledge Solutions, Siemens Medical Solutions, USA
Volker Tresp - Corporate Technology, Siemens AG, Germany
Kai Yu - NEC Lab America, USA
On the Value of Pairwise Constraints in Classification and Consistency
Jian Zhang - Purdue University, USA
Rong Yan - IBM Research, USA
Maximum Margin Clustering Made Practical
Kai Zhang - Hong Kong University of Science and Technology, Hong Kong
Ivor W. Tsang - Hong Kong University of Science and Technology, Hong Kong
James T. Kwok - Hong Kong University of Science and Technology, Hong Kong
Nonlinear Independent Component Analysis with Minimal Nonlinear Distortion
Kun Zhang - The Chinese University of Hong Kong, Hong Kong
Laiwan Chan - The Chinese University of Hong Kong, Hong Kong
Optimal Dimensionality of Metric Space for Classification
Wei Zhang - Department of Computer Science and Engineering, Fudan University, China
Xiangyang Xue - Department of Computer Science and Engineering, Fudan University, China
Zichen Sun - Department of Computer Science and Engineering, Fudan University, China
Yue-Fei Guo - Department of Computer Science and Engineering, Fudan University, China
Hong Lu - Department of Computer Science and Engineering, Fudan University, China
Conditional Random Fields for Multi-agent Reinforcement Learning
Xinhua Zhang - CSL, RSISE, Australian National University, and SML NICTA, Australia
Douglas Aberdeen - NICTA, Australian National University, Australia
S.V.N. Vishwanathan - SML NICTA, and CSL, RSISE, Australian National University, Australia
Spectral Feature Selection for Supervised and Unsupervised Learning
Zheng Zhao - Arizona State University, USA
Huan Liu - Arizona State University, USA
Spectral Clustering with Multiple Views
Dengyong Zhou - Microsoft Research, USA
Christopher J.C. Burges - Microsoft Research, USA
On the Relation Between Multi-Instance Learning and Semi-Supervised Learning
Zhi-Hua Zhou - Nanjing University, China
Jun-Ming Xu - Nanjing University, China
Dynamic Hierarchical Markov Random Fields and their Application to Web Data Extraction
Jun Zhu - Tsinghua University, P. R. China
Zaiqing Nie - Microsoft Research Asia, P. R. China
Bo Zhang - Tsinghua University, P. R. China
Ji-Rong Wen - Microsoft Research Asia, P. R. China
Transductive Support Vector Machines for Structured Variables
Alexander Zien - Max Planck Institute for Biological Cybernetics and Friedrich Miescher Laboratory, Germany
Ulf Brefeld - Max Planck Institute for Computer Science, Germany
Tobias Scheffer - Max Planck Institute for Computer Science, Germany
Multiclass Multiple Kernel Learning
Alexander Zien - MPI for Biological Cybernetics and Friedrich Miescher Laboratory, Tübingen, Germany
Cheng Soon Ong - MPI for Biological Cybernetics and Friedrich Miescher Laboratory, Tübingen, Germany