Continuous Optimization

Convergence of a Stochastic Gradient Method with Momentum for Non-Smooth Non-Convex Optimization ICML 2020 Convergence Rates of a Momentum Algorithm with Bounded Adaptive Step Size for Nonconvex Optimization ACML 2020 Convergence Rates of Gradient Descent and MM Algorithms for Bradley-Terry Models AISTATS 2020 Convergence Rates of Smooth Message Passing with Rounding in Entropy-Regularized MAP Inference AISTATS 2020 Convex optimization based on global lower second-order models NeurIPS 2020 COPT: Coordinated Optimal Transport on Graphs NeurIPS 2020 CORAL-DMOEA: Correlation Alignment-Based Information Transfer for Dynamic Multi-Objective Optimization (Student Abstract) AAAI 2020 Correspondence-Free Material Reconstruction using Sparse Surface Constraints CVPR 2020 Costly Zero Order Oracles COLT 2020 DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks NeurIPS 2020 Debiased Sinkhorn barycenters ICML 2020 Decisions, Counterfactual Explanations and Strategic Behavior NeurIPS 2020 Deep Implicit Volume Compression CVPR 2020 Deep Variational Instance Segmentation NeurIPS 2020 Defending with Shared Resources on a Network AAAI 2020 Depth Completion via Deep Basis Fitting WACV 2020 Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems JMLR 2020 Diffeomorphic Learning JMLR 2020 Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization NeurIPS 2020 Differentiable Likelihoods for Fast Inversion of ’Likelihood-Free’ Dynamical Systems ICML 2020 Dimension-Free Bounds for Chasing Convex Functions COLT 2020 Dinkelbach-Type Algorithm for Computing Quantal Stackelberg Equilibrium IJCAI 2020 DINO: Distributed Newton-Type Optimization Method ICML 2020 Discerning the Linear Convergence of ADMM for Structured Convex Optimization through the Lens of Variational Analysis JMLR 2020 Distributed Newton Can Communicate Less and Resist Byzantine Workers NeurIPS 2020