Optimization

Online Linear Optimization with Sparsity Constraints ALT 2019 Online Normalization for Training Neural Networks NeurIPS 2019 Online Pandora’s Boxes and Bandits AAAI 2019 Online Variance Reduction with Mixtures ICML 2019 Online-Within-Online Meta-Learning NeurIPS 2019 On Making Stochastic Classifiers Deterministic NeurIPS 2019 On NMT Search Errors and Model Errors: Cat Got Your Tongue? EMNLP 2019 On Nonlinear Spatial Filtering in Multichannel Speech Enhancement Interspeech 2019 On Robustness to Adversarial Examples and Polynomial Optimization NeurIPS 2019 On Sampling Complexity of the Semidefinite Affine Rank Feasibility Problem AAAI 2019 On Scalable and Efficient Computation of Large Scale Optimal Transport ICML 2019 On Single Source Robustness in Deep Fusion Models NeurIPS 2019 On Strength Adjustment for MCTS-Based Programs AAAI 2019 On The Classification-Distortion-Perception Tradeoff NeurIPS 2019 On the Computational Power of Online Gradient Descent COLT 2019 On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-Convex Optimization ICML 2019 On the Convergence and Robustness of Adversarial Training ICML 2019 On the convergence of single-call stochastic extra-gradient methods NeurIPS 2019 On the Convergence Rate of Training Recurrent Neural Networks NeurIPS 2019 On the Curved Geometry of Accelerated Optimization NeurIPS 2019 On the Design of Black-Box Adversarial Examples by Leveraging Gradient-Free Optimization and Operator Splitting Method ICCV 2019 On the Global Convergence of (Fast) Incremental Expectation Maximization Methods NeurIPS 2019 On the Global Optima of Kernelized Adversarial Representation Learning ICCV 2019 On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization ICML 2019 On the loss landscape of a class of deep neural networks with no bad local valleys ICLR 2019