Representation Learning

Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development NeurIPS 2010 Layer-wise analysis of deep networks with Gaussian kernels NeurIPS 2010 Learning Convolutional Feature Hierarchies for Visual Recognition NeurIPS 2010 Learning Efficient Markov Networks NeurIPS 2010 Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence JMLR 2010 Learning invariant features using the Transformed Indian Buffet Process NeurIPS 2010 Learning Multiple Tasks using Manifold Regularization NeurIPS 2010 Learning the context of a category NeurIPS 2010 Learning the Structure of Deep Sparse Graphical Models AISTATS 2010 Learning with Blocks: Composite Likelihood and Contrastive Divergence AISTATS 2010 Linear readout from a neural population with partial correlation data NeurIPS 2010 Locally Linear Denoising on Image Manifolds AISTATS 2010 Matched Gene Selection and Committee Classifier for Molecular Classification of Heterogeneous Diseases JMLR 2010 Moreau-Yosida Regularization for Grouped Tree Structure Learning NeurIPS 2010 Multitask Learning without Label Correspondences NeurIPS 2010 Noise-contrastive estimation: A new estimation principle for unnormalized statistical models AISTATS 2010 Nonparametric Tree Graphical Models AISTATS 2010 Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification NeurIPS 2010 On Learning with Integral Operators JMLR 2010 Online Learning for Matrix Factorization and Sparse Coding JMLR 2010 Online Learning in The Manifold of Low-Rank Matrices NeurIPS 2010 On Spectral Learning JMLR 2010 On the Convergence Properties of Contrastive Divergence AISTATS 2010 On the Convexity of Latent Social Network Inference NeurIPS 2010 Phoneme Recognition with Large Hierarchical Reservoirs NeurIPS 2010