Optimization

Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks ICML 2016 Normalized Spectral Map Synchronization NeurIPS 2016 NuC-MKL: A Convex Approach to Non Linear Multiple Kernel Learning AISTATS 2016 Object Tracking via Dual Linear Structured SVM and Explicit Feature Map CVPR 2016 On Benefits of Selection Diversity via Bilevel Exclusive Sparsity CVPR 2016 On Convergence of Model Parallel Proximal Gradient Algorithm for Stale Synchronous Parallel System AISTATS 2016 On Graduated Optimization for Stochastic Non-Convex Problems ICML 2016 Online (and Offline) Robust PCA: Novel Algorithms and Performance Guarantees AISTATS 2016 Online Convex Optimization with Unconstrained Domains and Losses NeurIPS 2016 Online learning in repeated auctions COLT 2016 Online Low-Rank Subspace Clustering by Basis Dictionary Pursuit ICML 2016 Online Stochastic Linear Optimization under One-bit Feedback ICML 2016 On Regularizing Rademacher Observation Losses NeurIPS 2016 On the Characterization of a Class of Fisher-Consistent Loss Functions and its Application to Boosting JMLR 2016 On the Influence of Momentum Acceleration on Online Learning JMLR 2016 On the Iteration Complexity of Oblivious First-Order Optimization Algorithms ICML 2016 Optimal Binary Classifier Aggregation for General Losses NeurIPS 2016 Optimal Black-Box Reductions Between Optimization Objectives NeurIPS 2016 Optimal Estimation and Completion of Matrices with Biclustering Structures JMLR 2016 Optimal Learning for Multi-pass Stochastic Gradient Methods NeurIPS 2016 Optimal Learning Rates for Localized SVMs JMLR 2016 Optimal rates for total variation denoising COLT 2016 Optimal Relative Pose With Unknown Correspondences CVPR 2016 Optimal Sparse Linear Encoders and Sparse PCA NeurIPS 2016 Optimal Statistical and Computational Rates for One Bit Matrix Completion AISTATS 2016