Optimization

Regularized Gradient Boosting NeurIPS 2019 Regularized Weighted Low Rank Approximation NeurIPS 2019 Regularizing Neural Networks via Stochastic Branch Layers ACML 2019 Reinforcement Learning based Curriculum Optimization for Neural Machine Translation NAACL 2019 Reinforcement Learning with Convex Constraints NeurIPS 2019 Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion JMLR 2019 Renyi Differentially Private ERM for Smooth Objectives AISTATS 2019 REPAIR: Removing Representation Bias by Dataset Resampling CVPR 2019 Reparameterizable Subset Sampling via Continuous Relaxations IJCAI 2019 Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help? ICCV 2019 RES-PCA: A Scalable Approach to Recovering Low-Rank Matrices CVPR 2019 Restoration of Non-Rigidly Distorted Underwater Images Using a Combination of Compressive Sensing and Local Polynomial Image Representations ICCV 2019 Rethinking Generative Mode Coverage: A Pointwise Guaranteed Approach NeurIPS 2019 Revisit Batch Normalization: New Understanding and Refinement via Composition Optimization AISTATS 2019 Revisiting Projection-Free Optimization for Strongly Convex Constraint Sets AAAI 2019 Revisiting the Softmax Bellman Operator: New Benefits and New Perspective ICML 2019 Reward Constrained Policy Optimization ICLR 2019 ReWE: Regressing Word Embeddings for Regularization of Neural Machine Translation Systems NAACL 2019 Riemannian Adaptive Optimization Methods ICLR 2019 Riemannian adaptive stochastic gradient algorithms on matrix manifolds ICML 2019 Robust and Communication-Efficient Collaborative Learning NeurIPS 2019 Robust Attribution Regularization NeurIPS 2019 Robust Bi-Tempered Logistic Loss Based on Bregman Divergences NeurIPS 2019 Robust descent using smoothed multiplicative noise AISTATS 2019 Robust Facial Landmark Detection via Occlusion-Adaptive Deep Networks CVPR 2019