Optimization

Deep Plug-And-Play Super-Resolution for Arbitrary Blur Kernels CVPR 2019 Deep Spectral Kernel Learning IJCAI 2019 Deep Tensor ADMM-Net for Snapshot Compressive Imaging ICCV 2019 DeepView: View Synthesis With Learned Gradient Descent CVPR 2019 DeepWave: A Recurrent Neural-Network for Real-Time Acoustic Imaging NeurIPS 2019 Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning ICML 2019 Defensive Quantization: When Efficiency Meets Robustness ICLR 2019 DepDist: Surface realization via regex and learned dependency-distance tolerance EMNLP 2019 Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems AISTATS 2019 Deriving Subgoals Autonomously to Accelerate Learning in Sparse Reward Domains AAAI 2019 Designing Optimal Binary Rating Systems AISTATS 2019 DetNAS: Backbone Search for Object Detection NeurIPS 2019 DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation NeurIPS 2019 Dichromatic Model Based Temporal Color Constancy for AC Light Sources CVPR 2019 Differentiable Cloth Simulation for Inverse Problems NeurIPS 2019 Differentiable Convex Optimization Layers NeurIPS 2019 Differentiable Game Mechanics JMLR 2019 Differentiable Physics and Stable Modes for Tool-Use and Manipulation Planning - Extended Abtract IJCAI 2019 Differentiable Ranking and Sorting using Optimal Transport NeurIPS 2019 Differentiable reservoir computing JMLR 2019 Differentiable Sampling with Flexible Reference Word Order for Neural Machine Translation NAACL 2019 Differential Inclusions for Modeling Nonsmooth ADMM Variants: A Continuous Limit Theory ICML 2019 Differentially Private Empirical Risk Minimization with Non-convex Loss Functions ICML 2019 Differentially Private Empirical Risk Minimization with Smooth Non-Convex Loss Functions: A Non-Stationary View AAAI 2019 Differentially Private Iterative Gradient Hard Thresholding for Sparse Learning IJCAI 2019