Representation Learning

A Family of Penalty Functions for Structured Sparsity NeurIPS 2010 A Regularization Approach to Nonlinear Variable Selection AISTATS 2010 Basis Construction from Power Series Expansions of Value Functions NeurIPS 2010 Bayesian Gaussian Process Latent Variable Model AISTATS 2010 Bayesian Learning in Sparse Graphical Factor Models via Variational Mean-Field Annealing JMLR 2010 b-Bit Minwise Hashing for Estimating Three-Way Similarities NeurIPS 2010 Beyond Actions: Discriminative Models for Contextual Group Activities NeurIPS 2010 Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm NeurIPS 2010 Collaborative Filtering on a Budget AISTATS 2010 Conditional Density Estimation via Least-Squares Density Ratio Estimation AISTATS 2010 Convex Structure Learning in Log-Linear Models: Beyond Pairwise Potentials AISTATS 2010 Cross Species Expression Analysis using a Dirichlet Process Mixture Model with Latent Matchings NeurIPS 2010 CUR from a Sparse Optimization Viewpoint NeurIPS 2010 Deciphering subsampled data: adaptive compressive sampling as a principle of brain communication NeurIPS 2010 Deep Coding Network NeurIPS 2010 Dense Message Passing for Sparse Principal Component Analysis AISTATS 2010 Dependent Indian Buffet Processes AISTATS 2010 Divisive Normalization: Justification and Effectiveness as Efficient Coding Transform NeurIPS 2010 Efficient algorithms for learning kernels from multiple similarity matrices with general convex loss functions NeurIPS 2010 Efficient Collapsed Gibbs Sampling for Latent Dirichlet Allocation ACML 2010 Efficient Learning of Deep Boltzmann Machines AISTATS 2010 Efficient Optimization for Discriminative Latent Class Models NeurIPS 2010 Energy Disaggregation via Discriminative Sparse Coding NeurIPS 2010 Evidence-Specific Structures for Rich Tractable CRFs NeurIPS 2010 Extended Bayesian Information Criteria for Gaussian Graphical Models NeurIPS 2010