Representation Learning

Sparse Features for PCA-Like Linear Regression NeurIPS 2011 Sparse Filtering NeurIPS 2011 Sparse Manifold Clustering and Embedding NeurIPS 2011 Spectral Methods for Learning Multivariate Latent Tree Structure NeurIPS 2011 Structural equations and divisive normalization for energy-dependent component analysis NeurIPS 2011 Structured sparse coding via lateral inhibition NeurIPS 2011 Structured Variable Selection with Sparsity-Inducing Norms JMLR 2011 Structure Learning for Optimization NeurIPS 2011 Testing a Bayesian Measure of Representativeness Using a Large Image Database NeurIPS 2011 The Indian Buffet Process: An Introduction and Review JMLR 2011 The Kernel Beta Process NeurIPS 2011 The Manifold Tangent Classifier NeurIPS 2011 The Sample Complexity of Dictionary Learning COLT 2011 The Sample Complexity of Dictionary Learning JMLR 2011 The Stationary Subspace Analysis Toolbox JMLR 2011 Thinning Measurement Models and Questionnaire Design NeurIPS 2011 Two Distributed-State Models For Generating High-Dimensional Time Series JMLR 2011 Two is better than one: distinct roles for familiarity and recollection in retrieving palimpsest memories NeurIPS 2011 Two-Layer Multiple Kernel Learning AISTATS 2011 Understanding the Intrinsic Memorability of Images NeurIPS 2011 Universality, Characteristic Kernels and RKHS Embedding of Measures JMLR 2011 Unsupervised learning models of primary cortical receptive fields and receptive field plasticity NeurIPS 2011 Variational Gaussian Process Dynamical Systems NeurIPS 2011 Variational Learning for Recurrent Spiking Networks NeurIPS 2011 A Discriminative Latent Model of Image Region and Object Tag Correspondence NeurIPS 2010