ICML 2010
159 papers
A Fast Natural Newton Method
Nicolas Le Roux, Andrew W. Fitzgibbon A Stick-Breaking Construction of the Beta Process
John W. Paisley, Aimee K. Zaas, Christopher W. Woods, Geoffrey S. Ginsburg, Lawrence Carin Active Learning for Networked Data
Mustafa Bilgic, Lilyana Mihalkova, Lise Getoor Active Risk Estimation
Christoph Sawade, Niels Landwehr, Steffen Bickel, Tobias Scheffer Asymptotic Analysis of Generative Semi-Supervised Learning
Joshua V. Dillon, Krishnakumar Balasubramanian, Guy Lebanon Budgeted Distribution Learning of Belief Net Parameters
Liuyang Li, Barnabás Póczos, Csaba Szepesvári, Russell Greiner Cognitive Models of Test-Item Effects in Human Category Learning
Xiaojin Zhu, Bryan R. Gibson, Kwang-Sung Jun, Timothy T. Rogers, Joseph Harrison, Chuck Kalish Comparing Clusterings in Space
Michael H. Coen, M. Hidayath Ansari, Nathanael Fillmore Continuous-Time Belief Propagation
Tal El-Hay, Ido Cohn, Nir Friedman, Raz Kupferman Deep Supervised T-Distributed Embedding
Martin Renqiang Min, Laurens van der Maaten, Zineng Yuan, Anthony J. Bonner, Zhaolei Zhang Detecting Large-Scale System Problems by Mining Console Logs
Wei Xu, Ling Huang, Armando Fox, David A. Patterson, Michael I. Jordan Discriminative Latent Variable Models for Object Detection
Pedro F. Felzenszwalb, Ross B. Girshick, David A. McAllester, Deva Ramanan Efficient Learning with Partially Observed Attributes
Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, Ohad Shamir Finite-Sample Analysis of LSTD
Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos Gaussian Process Change Point Models
Yunus Saatci, Ryan D. Turner, Carl Edward Rasmussen Generalization Bounds for Learning Kernels
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh Generalizing Apprenticeship Learning Across Hypothesis Classes
Thomas J. Walsh, Kaushik Subramanian, Michael L. Littman, Carlos Diuk Graded Multilabel Classification: The Ordinal Case
Weiwei Cheng, Krzysztof Dembczynski, Eyke Hüllermeier Hilbert Space Embeddings of Hidden Markov Models
Le Song, Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon, Alexander J. Smola Implicit Online Learning
Brian Kulis, Peter L. Bartlett Interactive Submodular Set Cover
Andrew Guillory, Jeff A. Bilmes Internal Rewards Mitigate Agent Boundedness
Jonathan Sorg, Satinder Singh, Richard L. Lewis Label Ranking Methods Based on the Plackett-Luce Model
Weiwei Cheng, Krzysztof Dembczynski, Eyke Hüllermeier Large Scale Max-Margin Multi-Label Classification with Priors
Bharath Hariharan, Lihi Zelnik-Manor, S. V. N. Vishwanathan, Manik Varma Learning Efficiently with Approximate Inference via Dual Losses
Ofer Meshi, David A. Sontag, Tommi S. Jaakkola, Amir Globerson Local Minima Embedding
Minyoung Kim, Fernando De la Torre Metric Learning to Rank
Brian McFee, Gert R. G. Lanckriet Mixed Membership Matrix Factorization
Lester W. Mackey, David J. Weiss, Michael I. Jordan Multi-Class Pegasos on a Budget
Zhuang Wang, Koby Crammer, Slobodan Vucetic Non-Local Contrastive Objectives
David Vickrey, Cliff Chiung-Yu Lin, Daphne Koller Nonparametric Return Distribution Approximation for Reinforcement Learning
Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya, Toshiyuki Tanaka On the Consistency of Ranking Algorithms
John C. Duchi, Lester W. Mackey, Michael I. Jordan Online Learning for Group Lasso
Haiqin Yang, Zenglin Xu, Irwin King, Michael R. Lyu Online Streaming Feature Selection
Xindong Wu, Kui Yu, Hao Wang, Wei Ding Power Iteration Clustering
Frank Lin, William W. Cohen Proximal Methods for Sparse Hierarchical Dictionary Learning
Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis R. Bach Random Spanning Trees and the Prediction of Weighted Graphs
Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella Robust Formulations for Handling Uncertainty in Kernel Matrices
Sahely Bhadra, Sourangshu Bhattacharya, Chiranjib Bhattacharyya, Aharon Ben-Tal Simple and Efficient Multiple Kernel Learning by Group Lasso
Zenglin Xu, Rong Jin, Haiqin Yang, Irwin King, Michael R. Lyu Spherical Topic Models
Joseph Reisinger, Austin Waters, Bryan Silverthorn, Raymond J. Mooney Structured Output Learning with Indirect Supervision
Ming-Wei Chang, Vivek Srikumar, Dan Goldwasser, Dan Roth The Margin Perceptron with Unlearning
Constantinos Panagiotakopoulos, Petroula Tsampouka Total Variation, Cheeger Cuts
Arthur Szlam, Xavier Bresson Toward Off-Policy Learning Control with Function Approximation
Hamid Reza Maei, Csaba Szepesvári, Shalabh Bhatnagar, Richard S. Sutton Two-Stage Learning Kernel Algorithms
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh