Optimization

SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization ICML 2016 SDP Relaxation with Randomized Rounding for Energy Disaggregation NeurIPS 2016 SEBOOST - Boosting Stochastic Learning Using Subspace Optimization Techniques NeurIPS 2016 Semi-Supervised Joint Enhancement of Spectral and Cepstral Sequences of Noisy Speech Interspeech 2016 Semi-Supervised Training in Deep Learning Acoustic Model Interspeech 2016 Shortlist Selection With Residual-Aware Distance Estimator for K-Nearest Neighbor Search CVPR 2016 Simultaneous Safe Screening of Features and Samples in Doubly Sparse Modeling ICML 2016 SNR-Based Progressive Learning of Deep Neural Network for Speech Enhancement Interspeech 2016 Soft-Segmentation Guided Object Motion Deblurring CVPR 2016 Solving Marginal MAP Problems with NP Oracles and Parity Constraints NeurIPS 2016 Solving Random Systems of Quadratic Equations via Truncated Generalized Gradient Flow NeurIPS 2016 Solving Ridge Regression using Sketched Preconditioned SVRG ICML 2016 Solving Small-Piece Jigsaw Puzzles by Growing Consensus CVPR 2016 Sparse Coding and Dictionary Learning With Linear Dynamical Systems CVPR 2016 Sparse Nonlinear Regression: Parameter Estimation under Nonconvexity ICML 2016 Split LBI: An Iterative Regularization Path with Structural Sparsity NeurIPS 2016 Starting Small - Learning with Adaptive Sample Sizes ICML 2016 Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues ICML 2016 Stochastic Block BFGS: Squeezing More Curvature out of Data ICML 2016 Stochastic Gradient Methods for Distributionally Robust Optimization with f-divergences NeurIPS 2016 Stochastic Online AUC Maximization NeurIPS 2016 Stochastic Optimization for Large-scale Optimal Transport NeurIPS 2016 Stochastic Optimization for Multiview Representation Learning using Partial Least Squares ICML 2016 Stochastic Structured Prediction under Bandit Feedback NeurIPS 2016 Stochastic Three-Composite Convex Minimization NeurIPS 2016