← Core Methods
Machine Learning › Core Methods ›

Representation Learning

18863 directly classified papers

Papers per year

Papers

Deterministic Independent Component Analysis ICML 2015
Geometric Conditions for Subspace-Sparse Recovery ICML 2015
Information Geometry and Minimum Description Length Networks ICML 2015
A Deeper Look at Planning as Learning from Replay ICML 2015
Variational Generative Stochastic Networks with Collaborative Shaping ICML 2015
Rademacher Observations, Private Data, and Boosting ICML 2015
A Stochastic PCA and SVD Algorithm with an Exponential Convergence Rate ICML 2015
Finding Linear Structure in Large Datasets with Scalable Canonical Correlation Analysis ICML 2015
On the Relationship between Sum-Product Networks and Bayesian Networks ICML 2015
Multi-view Sparse Co-clustering via Proximal Alternating Linearized Minimization ICML 2015
Universal Value Function Approximators ICML 2015
Towards a Lower Sample Complexity for Robust One-bit Compressed Sensing ICML 2015
Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams ICML 2015
Classification with Low Rank and Missing Data ICML 2015
Tensor Factorization via Matrix Factorization AISTATS 2015
Cross-domain recommendation without shared users or items by sharing latent vector distributions AISTATS 2015
One-bit Compressed Sensing with the k-Support Norm AISTATS 2015
A totally unimodular view of structured sparsity AISTATS 2015
Multi-Manifold Modeling in Non-Euclidean spaces AISTATS 2015
Consistent Collective Matrix Completion under Joint Low Rank Structure AISTATS 2015
Understanding and Evaluating Sparse Linear Discriminant Analysis AISTATS 2015
Learning Overcomplete Latent Variable Models through Tensor Methods COLT 2015
Eigenwords: Spectral Word Embeddings JMLR 2015
Online Tensor Methods for Learning Latent Variable Models JMLR 2015
Learning Transformations for Clustering and Classification JMLR 2015