- A Minimum Description Length Framework for Unsupervised Learning
- Active Collaborative Filtering Craig Boutilier and Richard S. Zemel and Ben Marlin
- Multiscale Conditional Random Fields for Image Labeling Xuming He Richard S. Zemel Miguel
- To appear in: Neural Computation, 7:3, 1995. Competition and Multiple Cause Models
- Learning Hybrid Models for Image Annotation with Partially Labeled Data
- A Model for Encoding Multiple Object Motions and Self-Motion in Area MST of Primate Visual Cortex
- To appear in: Advances in Neural Information Processing Systems 12, S. A. Solla, T. K. Leen & uller (eds.), MIT Press (2000).
- To appear in: R. HechtNeilsen (Ed.), Theories of Cortical Processing. SpringerVerlag. Cortical Belief Networks
- Curriculum Vitae Richard S. Zemel
- Efficient Message Passing with High
- Generative versus discriminative training of RBMs for classification of fMRI images
- Latent Topic Random Fields: Learning using a taxonomy of labels University of Toronto
- Learning Flexible Features for Conditional Random Liam Stewart, Xuming He, Richard S. Zemel
- LETTER Communicated by Alexandre Pouget Fast Population Coding
- Online Queries for Collaborative Filtering Craig Boutilier and Richard S. Zemel
- LETTER Communicated by Andreas Tolias Population Coding with Motion Energy Filters
- 4.3. EXPERIMENTAL RESULTS 71 Figure 4.6: This figure shows the incoming and outgoing weights for the 30 representation units
- Characterizing response behavior in multi-sensory perception with conflicting cues
- Multiscale Conditional Random Fields for Image Labeling Xuming He Richard S. Zemel Miguel A. Carreira-Perpi~nan
- ExperienceDependent Perceptual Grouping and ObjectBased Attention
- Learning stick-figure models using nonparametric Bayesian priors over trees Edward W. Meeds, David A. Ross, Richard S. Zemel, and Sam T. Roweis
- BoltzRank: Learning to Maximize Expected Ranking Gain Maksims N. Volkovs mvolkovs@cs.toronto.edu
- Communicated by Terrence Sanger Probabilistic Interpretation of Population Codes
- LETTER Communicated by David Touretzky Localist Attractor Networks
- Online Queries for Collaborative Filtering Craig Boutilier and Richard S. Zemel
- Minimizing Description Length in an Unsupervised Neural Network
- 5.4. EXPERIMENTAL RESULTS 91 Figure 5.10: This figure shows the outgoing weights for a CVQ network with 5 VQs and 6 units per
- Probabilistic Sequential Independent Components Analysis Max Welling
- A Framework for Optimizing Paper Matching Laurent Charlin
- Recommender Systems: Missing Data and Statistical Model Estimation Benjamin M. Marlin
- Fairness Through Awareness Cynthia Dwork
- Dynamic Cue Combination in Distributional Population Code Networks
