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Representation Learning

18863 directly classified papers

Papers per year

Papers

Kernel Hyperalignment NIPS 2012
Matrix reconstruction with the local max norm NIPS 2012
Supervised Dimension Reduction with Topic Models ACML 2012
High-Dimensional Structured Feature Screening Using Binary Markov Random Fields AISTATS 2012
Learning with Recursive Perceptual Representations NIPS 2012
Dimensionality Reduction for Spectral Clustering AISTATS 2011
On Learning Discrete Graphical Models using Greedy Methods NIPS 2011
Computationally Efficient Sufficient Dimension Reduction via Squared-Loss Mutual Information ACML 2011
Deep Learners Benefit More from Out-of-Distribution Examples AISTATS 2011
Global Solution of Fully-Observed Variational Bayesian Matrix Factorization is Column-Wise Independent NIPS 2011
Error Analysis of Laplacian Eigenmaps for Semi-supervised Learning AISTATS 2011
Sparse Manifold Clustering and Embedding NIPS 2011
Probabilistic Modeling of Dependencies Among Visual Short-Term Memory Representations NIPS 2011
Regularized Laplacian Estimation and Fast Eigenvector Approximation NIPS 2011
Generalized Lasso based Approximation of Sparse Coding for Visual Recognition NIPS 2011
Sparse Filtering NIPS 2011
Spectral Methods for Learning Multivariate Latent Tree Structure NIPS 2011
Query-Aware MCMC NIPS 2011
Learning Anchor Planes for Classification NIPS 2011
A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm NIPS 2011
Structure Learning for Optimization NIPS 2011
Data Skeletonization via Reeb Graphs NIPS 2011
Learning Sparse Representations of High Dimensional Data on Large Scale Dictionaries NIPS 2011
A Non-Parametric Approach to Dynamic Programming NIPS 2011
Bayesian Spike-Triggered Covariance Analysis NIPS 2011