ICML 2008
157 papers
A Distance Model for Rhythms
Jean-François Paiement, Yves Grandvalet, Samy Bengio, Douglas Eck A Dual Coordinate Descent Method for Large-Scale Linear SVM
Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin, S. Sathiya Keerthi, S. Sundararajan A Quasi-Newton Approach to Non-Smooth Convex Optimization
Jin Yu, S. V. N. Vishwanathan, Simon Günter, Nicol N. Schraudolph A Semiparametric Statistical Approach to Model-Free Policy Evaluation
Tsuyoshi Ueno, Motoaki Kawanabe, Takeshi Mori, Shin-ichi Maeda, Shin Ishii Active Kernel Learning
Steven C. H. Hoi, Rong Jin Active Reinforcement Learning
Arkady Epshteyn, Adam Vogel, Gerald DeJong An HDP-HMM for Systems with State Persistence
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky Apprenticeship Learning Using Linear Programming
Umar Syed, Michael H. Bowling, Robert E. Schapire Automatic Discovery and Transfer of MAXQ Hierarchies
Neville Mehta, Soumya Ray, Prasad Tadepalli, Thomas G. Dietterich Beam Sampling for the Infinite Hidden Markov Model
Jurgen Van Gael, Yunus Saatci, Yee Whye Teh, Zoubin Ghahramani Boosting with Incomplete Information
Gholamreza Haffari, Yang Wang, Shaojun Wang, Greg Mori, Feng Jiao Closed-Form Supervised Dimensionality Reduction with Generalized Linear Models
Irina Rish, Genady Grabarnik, Guillermo A. Cecchi, Francisco Pereira, Geoffrey J. Gordon Composite Kernel Learning
Marie Szafranski, Yves Grandvalet, Alain Rakotomamonjy Confidence-Weighted Linear Classification
Mark Dredze, Koby Crammer, Fernando Pereira Deep Learning via Semi-Supervised Embedding
Jason Weston, Frédéric Ratle, Ronan Collobert Democratic Approximation of Lexicographic Preference Models
Fusun Yaman, Thomas J. Walsh, Michael L. Littman, Marie desJardins Empirical Bernstein Stopping
Volodymyr Mnih, Csaba Szepesvári, Jean-Yves Audibert Estimating Labels from Label Proportions
Novi Quadrianto, Alexander J. Smola, Tibério S. Caetano, Quoc V. Le Exploration Scavenging
John Langford, Alexander L. Strehl, Jennifer Wortman Extracting and Composing Robust Features with Denoising Autoencoders
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pierre-Antoine Manzagol Fast Incremental Proximity Search in Large Graphs
Purnamrita Sarkar, Andrew W. Moore, Amit Prakash Fully Distributed EM for Very Large Datasets
Jason Andrew Wolfe, Aria Haghighi, Dan Klein Hierarchical Kernel Stick-Breaking Process for Multi-Task Image Analysis
Qi An, Chunping Wang, Ivo Shterev, Eric Wang, Lawrence Carin, David B. Dunson Large Scale Manifold Transduction
Michael Karlen, Jason Weston, Ayse Erkan, Ronan Collobert Learning Diverse Rankings with Multi-Armed Bandits
Filip Radlinski, Robert Kleinberg, Thorsten Joachims Maximum Likelihood Rule Ensembles
Krzysztof Dembczynski, Wojciech Kotlowski, Roman Slowinski Metric Embedding for Kernel Classification Rules
Bharath K. Sriperumbudur, Omer A. Lang, Gert R. G. Lanckriet Multi-Task Learning for HIV Therapy Screening
Steffen Bickel, Jasmina Bogojeska, Thomas Lengauer, Tobias Scheffer Multiple Instance Ranking
Charles Bergeron, Jed Zaretzki, Curt M. Breneman, Kristin P. Bennett No-Regret Learning in Convex Games
Geoffrey J. Gordon, Amy Greenwald, Casey Marks Nonextensive Entropic Kernels
André F. T. Martins, Mário A. T. Figueiredo, Pedro M. Q. Aguiar, Noah A. Smith, Eric P. Xing On Partial Optimality in Multi-Label MRFs
Pushmeet Kohli, Alexander Shekhovtsov, Carsten Rother, Vladimir Kolmogorov, Philip H. S. Torr Polyhedral Classifier for Target Detection: A Case Study: Colorectal Cancer
Murat Dundar, Matthias Wolf, Sarang Lakare, Marcos Salganicoff, Vikas C. Raykar Privacy-Preserving Reinforcement Learning
Jun Sakuma, Shigenobu Kobayashi, Rebecca N. Wright Rank Minimization via Online Learning
Raghu Meka, Prateek Jain, Constantine Caramanis, Inderjit S. Dhillon Robust Matching and Recognition Using Context-Dependent Kernels
Hichem Sahbi, Jean-Yves Audibert, Jaonary Rabarisoa, Renaud Keriven Self-Taught Clustering
Wenyuan Dai, Qiang Yang, Gui-Rong Xue, Yong Yu Space-Indexed Dynamic Programming: Learning to Follow Trajectories
J. Zico Kolter, Adam Coates, Andrew Y. Ng, Yi Gu, Charles DuHadway Sparse Multiscale Gaussian Process Regression
Christian Walder, Kwang In Kim, Bernhard Schölkopf Spectral Clustering with Inconsistent Advice
Tom Coleman, James Saunderson, Anthony Wirth Stability of Transductive Regression Algorithms
Corinna Cortes, Mehryar Mohri, Dmitry Pechyony, Ashish Rastogi Statistical Models for Partial Membership
Katherine A. Heller, Sinead Williamson, Zoubin Ghahramani Strategy Evaluation in Extensive Games with Importance Sampling
Michael H. Bowling, Michael Johanson, Neil Burch, Duane Szafron Tailoring Density Estimation via Reproducing Kernel Moment Matching
Le Song, Xinhua Zhang, Alexander J. Smola, Arthur Gretton, Bernhard Schölkopf The Projectron: A Bounded Kernel-Based Perceptron
Francesco Orabona, Joseph Keshet, Barbara Caputo The Skew Spectrum of Graphs
Risi Kondor, Karsten M. Borgwardt Topologically-Constrained Latent Variable Models
Raquel Urtasun, David J. Fleet, Andreas Geiger, Jovan Popovic, Trevor Darrell, Neil D. Lawrence Transfer of Samples in Batch Reinforcement Learning
Alessandro Lazaric, Marcello Restelli, Andrea Bonarini