Optimization

MinMax Methods for Optimal Transport and Beyond: Regularization, Approximation and Numerics NeurIPS 2020 Min-Max Optimization without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks ICML 2020 MIPaaL: Mixed Integer Program as a Layer AAAI 2020 Missing Data Imputation using Optimal Transport ICML 2020 Mitigating Manipulation in Peer Review via Randomized Reviewer Assignments NeurIPS 2020 Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions NeurIPS 2020 MixedAD: A Scalable Algorithm for Detecting Mixed Anomalies in Attributed Graphs AAAI 2020 Mixed-Variable Bayesian Optimization IJCAI 2020 M-LVC: Multiple Frames Prediction for Learned Video Compression CVPR 2020 Mnemonics Training: Multi-Class Incremental Learning Without Forgetting CVPR 2020 Model-Based Reinforcement Learning with a Generative Model is Minimax Optimal COLT 2020 Modeling and Optimization Trade-off in Meta-learning NeurIPS 2020 Model Inversion Networks for Model-Based Optimization NeurIPS 2020 Model-Predictive Control via Cross-Entropy and Gradient-Based Optimization L4DC 2020 Modulating Surrogates for Bayesian Optimization ICML 2020 Momentum-Based Policy Gradient Methods ICML 2020 Momentum Improves Normalized SGD ICML 2020 Monotone operator equilibrium networks NeurIPS 2020 Monte-Carlo Tree Search as Regularized Policy Optimization ICML 2020 Monte-Carlo Tree Search in Continuous Action Spaces with Value Gradients AAAI 2020 MSG-GAN: Multi-Scale Gradients for Generative Adversarial Networks CVPR 2020 Multiagent Rollout and Policy Iteration for POMDP with Application to Multi-Robot Repair Problems CoRL 2020 Multichannel Color Image Denoising via Weighted Schatten p-norm Minimization IJCAI 2020 Multiclass Neural Network Minimization via Tropical Newton Polytope Approximation ICML 2020 Multidimensional Shape Constraints ICML 2020