Representation Learning

Hierarchical Modeling of Local Image Features through L_p-Nested Symmetric Distributions NeurIPS 2009 Inter-domain Gaussian Processes for Sparse Inference using Inducing Features NeurIPS 2009 Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions NeurIPS 2009 Kernel Methods for Deep Learning NeurIPS 2009 Learning Approximate Sequential Patterns for Classification JMLR 2009 Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data NeurIPS 2009 Learning from Neighboring Strokes: Combining Appearance and Context for Multi-Domain Sketch Recognition NeurIPS 2009 Learning in Markov Random Fields using Tempered Transitions NeurIPS 2009 Learning models of object structure NeurIPS 2009 Learning Non-Linear Combinations of Kernels NeurIPS 2009 Learning to Hash with Binary Reconstructive Embeddings NeurIPS 2009 Learning transport operators for image manifolds NeurIPS 2009 Learning with Compressible Priors NeurIPS 2009 Linearly constrained Bayesian matrix factorization for blind source separation NeurIPS 2009 Locality-sensitive binary codes from shift-invariant kernels NeurIPS 2009 Low-Rank Kernel Learning with Bregman Matrix Divergences JMLR 2009 Manifold Regularization for SIR with Rate Root-n Convergence NeurIPS 2009 Matrix Completion from Noisy Entries NeurIPS 2009 Measuring Invariances in Deep Networks NeurIPS 2009 Modeling Social Annotation Data with Content Relevance using a Topic Model NeurIPS 2009 Modelling Relational Data using Bayesian Clustered Tensor Factorization NeurIPS 2009 Multi-Label Prediction via Sparse Infinite CCA NeurIPS 2009 No evidence for active sparsification in the visual cortex NeurIPS 2009 Nonlinear Learning using Local Coordinate Coding NeurIPS 2009 Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations NeurIPS 2009