Representation Learning

Scalable Non-linear Learning with Adaptive Polynomial Expansions NeurIPS 2014 Scale-space Processing Using Polynomial Representations CVPR 2014 Self-Adaptable Templates for Feature Coding NeurIPS 2014 Self-Paced Learning with Diversity NeurIPS 2014 Semi-Supervised Coupled Dictionary Learning for Person Re-identification CVPR 2014 Sensory Integration and Density Estimation NeurIPS 2014 SerialRank: Spectral Ranking using Seriation NeurIPS 2014 Simultaneous Model Selection and Optimization through Parameter-free Stochastic Learning NeurIPS 2014 Simultaneous Twin Kernel Learning using Polynomial Transformations for Structured Prediction CVPR 2014 Smooth Representation Clustering CVPR 2014 Sparse Bayesian structure learning with “dependent relevance determination” priors NeurIPS 2014 Sparse Dictionary Learning for Edit Propagation of High-Resolution Images CVPR 2014 Sparse Factor Analysis for Learning and Content Analytics JMLR 2014 Sparse meta-Gaussian information bottleneck ICML 2014 Sparse Reinforcement Learning via Convex Optimization ICML 2014 Spectral k-Support Norm Regularization NeurIPS 2014 Spectral Learning of Latent-Variable PCFGs: Algorithms and Sample Complexity JMLR 2014 Spectral Learning of Mixture of Hidden Markov Models NeurIPS 2014 Spectral Methods for Supervised Topic Models NeurIPS 2014 Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery ICML 2014 Stable and Efficient Representation Learning with Nonnegativity Constraints ICML 2014 State Representation Learning in Robotics: Using Prior Knowledge about Physical Interaction RSS 2014 Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices ICML 2014 Strokelets: A Learned Multi-Scale Representation for Scene Text Recognition CVPR 2014 Structured Low-Rank Matrix Factorization: Optimality, Algorithm, and Applications to Image Processing ICML 2014