Optimization

Differentiable Top-k with Optimal Transport NeurIPS 2020 Differentially Private Clustering: Tight Approximation Ratios NeurIPS 2020 Differentially Private Learning with Small Public Data AAAI 2020 Differentiating through the Fréchet Mean ICML 2020 Differentiation of Blackbox Combinatorial Solvers ICLR 2020 DiffTaichi: Differentiable Programming for Physical Simulation ICLR 2020 Directional Pruning of Deep Neural Networks NeurIPS 2020 Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces NeurIPS 2020 Direct Quantization for Training Highly Accurate Low Bit-width Deep Neural Networks IJCAI 2020 DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction NeurIPS 2020 Discrete Embedding for Latent Networks IJCAI 2020 Discrete Model Compression With Resource Constraint for Deep Neural Networks CVPR 2020 Discriminative Feature Selection via A Structured Sparse Subspace Learning Module IJCAI 2020 DISK: Learning local features with policy gradient NeurIPS 2020 Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression AAAI 2020 DIST: Rendering Deep Implicit Signed Distance Function With Differentiable Sphere Tracing CVPR 2020 Distributed Newton Can Communicate Less and Resist Byzantine Workers NeurIPS 2020 Distributed Stochastic Gradient Descent with Event-Triggered Communication AAAI 2020 Distributionally Robust Bayesian Optimization AISTATS 2020 Distributionally Robust Counterfactual Risk Minimization AAAI 2020 Distributionally Robust Federated Averaging NeurIPS 2020 Distributionally Robust Formulation and Model Selection for the Graphical Lasso AISTATS 2020 Distributionally Robust Local Non-parametric Conditional Estimation NeurIPS 2020 Distributionally Robust Neural Networks ICLR 2020 Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits ICML 2020