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Representation Learning

20,822 papers

Papers per year

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101
309
2011
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Papers

Additive Approximations in High Dimensional Nonparametric Regression via the SALSA ICML 2016
Why Regularized Auto-Encoders learn Sparse Representation? ICML 2016
The Information Sieve ICML 2016
The Variational Nystrom method for large-scale spectral problems ICML 2016
A Kernelized Stein Discrepancy for Goodness-of-fit Tests ICML 2016
Variable Elimination in the Fourier Domain ICML 2016
Hierarchical Variational Models ICML 2016
Hierarchical Span-Based Conditional Random Fields for Labeling and Segmenting Events in Wearable Sensor Data Streams ICML 2016
Structure Learning of Partitioned Markov Networks ICML 2016
A Neural Autoregressive Approach to Collaborative Filtering ICML 2016
Polynomial Networks and Factorization Machines: New Insights and Efficient Training Algorithms ICML 2016
Analysis of Variational Bayesian Factorizations for Sparse and Low-Rank Estimation ICML 2016
Boolean Matrix Factorization and Noisy Completion via Message Passing ICML 2016
Low-rank Solutions of Linear Matrix Equations via Procrustes Flow ICML 2016
Structured Prediction Energy Networks ICML 2016
Representational Similarity Learning with Application to Brain Networks ICML 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning ICML 2016
Markov Latent Feature Models ICML 2016
A Subspace Learning Approach for High Dimensional Matrix Decomposition with Efficient Column/Row Sampling ICML 2016
Factored Temporal Sigmoid Belief Networks for Sequence Learning ICML 2016
Non-negative Matrix Factorization under Heavy Noise ICML 2016
Rich Component Analysis ICML 2016
Dictionary Learning for Massive Matrix Factorization ICML 2016
Stochastic Optimization for Multiview Representation Learning using Partial Least Squares ICML 2016
Nonparametric Canonical Correlation Analysis ICML 2016