Papers
Measuring Neural Synchrony by Message Passing
Justin Dauwels, François Vialatte, Tomasz Rutkowski et al.
Scene Segmentation with CRFs Learned from Partially Labeled Images
Bill Triggs, Jakob J. Verbeek
A Game-Theoretic Approach to Apprenticeship Learning
Umar Syed, Robert E. Schapire
Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning
Gerald Tesauro, Rajarshi Das, Hoi Chan et al.
A Risk Minimization Principle for a Class of Parzen Estimators
Kristiaan Pelckmans, Johan Suykens, Bart D. Moor
Receding Horizon Differential Dynamic Programming
Yuval Tassa, Tom Erez, William D. Smart
Sparse Feature Learning for Deep Belief Networks
Marc'aurelio Ranzato, Y-lan Boureau, Yann L. Cun
Boosting the Area under the ROC Curve
Phil Long, Rocco Servedio
Message Passing for Max-weight Independent Set
Sujay Sanghavi, Devavrat Shah, Alan S. Willsky
Efficient Convex Relaxation for Transductive Support Vector Machine
Zenglin Xu, Rong Jin, Jianke Zhu et al.
Learning to classify complex patterns using a VLSI network of spiking neurons
Srinjoy Mitra, Giacomo Indiveri, Stefano Fusi
Automatic Generation of Social Tags for Music Recommendation
Douglas Eck, Paul Lamere, Thierry Bertin-mahieux et al.
A probabilistic model for generating realistic lip movements from speech
Gwenn Englebienne, Tim Cootes, Magnus Rattray
Learning with Transformation Invariant Kernels
Christian Walder, Olivier Chapelle
Support Vector Machine Classification with Indefinite Kernels
Ronny Luss, Alexandre D'aspremont
Iterative Non-linear Dimensionality Reduction with Manifold Sculpting
Michael Gashler, Dan Ventura, Tony Martinez
The Price of Bandit Information for Online Optimization
Varsha Dani, Sham M. Kakade, Thomas P. Hayes
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashima et al.
A Randomized Algorithm for Large Scale Support Vector Learning
Krishnan Kumar, Chiru Bhattacharya, Ramesh Hariharan
McRank: Learning to Rank Using Multiple Classification and Gradient Boosting
Ping Li, Qiang Wu, Christopher J. Burges
Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations
M. M. Mahmud, Sylvian Ray
Online Linear Regression and Its Application to Model-Based Reinforcement Learning
Alexander L. Strehl, Michael L. Littman
Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms
Dominik Endres, Mike Oram, Johannes Schindelin et al.
Active Preference Learning with Discrete Choice Data
Brochu Eric, Nando D. Freitas, Abhijeet Ghosh
Retrieved context and the discovery of semantic structure
Vinayak Rao, Marc Howard