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Representation Learning

18863 directly classified papers

Papers per year

Papers

Structured Variable Selection with Sparsity-Inducing Norms JMLR 2011
Two Distributed-State Models For Generating High-Dimensional Time Series JMLR 2011
Kernel Analysis of Deep Networks JMLR 2011
The Sample Complexity of Dictionary Learning COLT 2011
Deep Learners Benefit More from Out-of-Distribution Examples AISTATS 2011
A Spike and Slab Restricted Boltzmann Machine AISTATS 2011
Discussion of “The Neural Autoregressive Distribution Estimator” AISTATS 2011
Learning Class-relevant Features and Class-irrelevant Features via a Hybrid third-order RBM AISTATS 2011
Spectral Regularization Algorithms for Learning Large Incomplete Matrices JMLR 2010
Information Retrieval Perspective to Nonlinear Dimensionality Reduction for Data Visualization JMLR 2010
Efficient Collapsed Gibbs Sampling for Latent Dirichlet Allocation ACML 2010
Locally Linear Denoising on Image Manifolds AISTATS 2010
Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images AISTATS 2010
Factorized Orthogonal Latent Spaces AISTATS 2010
Efficient Learning of Deep Boltzmann Machines AISTATS 2010
Simple Exponential Family PCA AISTATS 2010
On the Convergence Properties of Contrastive Divergence AISTATS 2010
Understanding the difficulty of training deep feedforward neural networks AISTATS 2010
Collaborative Filtering on a Budget AISTATS 2010
Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion JMLR 2010
Practical Approaches to Principal Component Analysis in the Presence of Missing Values JMLR 2010
Graph Kernels JMLR 2010
On Spectral Learning JMLR 2010
Generalized Power Method for Sparse Principal Component Analysis JMLR 2010
On Learning with Integral Operators JMLR 2010