Representation Learning

Practical Approaches to Principal Component Analysis in the Presence of Missing Values JMLR 2010 Predictive State Temporal Difference Learning NeurIPS 2010 Predictive Subspace Learning for Multi-view Data: a Large Margin Approach NeurIPS 2010 Probabilistic Multi-Task Feature Selection NeurIPS 2010 Reduced-Rank Hidden Markov Models AISTATS 2010 Robust PCA via Outlier Pursuit NeurIPS 2010 Self-Paced Learning for Latent Variable Models NeurIPS 2010 Shadow Dirichlet for Restricted Probability Modeling NeurIPS 2010 Short-term memory in neuronal networks through dynamical compressed sensing NeurIPS 2010 Simple Exponential Family PCA AISTATS 2010 Sparse Coding for Learning Interpretable Spatio-Temporal Primitives NeurIPS 2010 Sparse Inverse Covariance Selection via Alternating Linearization Methods NeurIPS 2010 Spectral Regularization Algorithms for Learning Large Incomplete Matrices JMLR 2010 Spike timing-dependent plasticity as dynamic filter NeurIPS 2010 Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion JMLR 2010 Structured Determinantal Point Processes NeurIPS 2010 Supervised Dimension Reduction Using Bayesian Mixture Modeling AISTATS 2010 The Coding Divergence for Measuring the Complexity of Separating Two Sets ACML 2010 The Feature Selection Path in Kernel Methods AISTATS 2010 The Maximal Causes of Natural Scenes are Edge Filters NeurIPS 2010 Tiled convolutional neural networks NeurIPS 2010 Towards Understanding Situated Natural Language AISTATS 2010 Tree-Structured Stick Breaking for Hierarchical Data NeurIPS 2010 Understanding the difficulty of training deep feedforward neural networks AISTATS 2010 Unsupervised Kernel Dimension Reduction NeurIPS 2010