Mathematics & Optimization

Large-Scale Methods for Distributionally Robust Optimization NeurIPS 2020 Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems COLT 2020 Latent Bandits Revisited NeurIPS 2020 Layered Sampling for Robust Optimization Problems ICML 2020 Lazy-CFR: fast and near-optimal regret minimization for extensive games with imperfect information ICLR 2020 LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments ICML 2020 Leading Multi-Agent Teams to Multiple Goals While Maintaining Communication RSS 2020 Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning ACML 2020 Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition ICML 2020 Learning Algebraic Multigrid Using Graph Neural Networks ICML 2020 Learning and Solving Regular Decision Processes IJCAI 2020 Learning-Augmented Data Stream Algorithms ICLR 2020 Learning Augmented Energy Minimization via Speed Scaling NeurIPS 2020 Learning-based Stochastic Model Predictive Control with State-Dependent Uncertainty L4DC 2020 Learning Combinatorial Solver for Graph Matching CVPR 2020 Learning Composable Energy Surrogates for PDE Order Reduction NeurIPS 2020 Learning Continuous System Dynamics from Irregularly-Sampled Partial Observations NeurIPS 2020 Learning Convex Optimization Control Policies L4DC 2020 Learning decomposable models by coarsening PGM 2020 Learning discrete distributions: user vs item-level privacy NeurIPS 2020 Learning discrete distributions with infinite support NeurIPS 2020 Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration NeurIPS 2020 Learning Dynamical Systems with Side Information L4DC 2020 Learning Dynamic Relationships for 3D Human Motion Prediction CVPR 2020 Learning Entangled Single-Sample Gaussians in the Subset-of-Signals Model COLT 2020