Optimization

Learning Stabilizing Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory L4DC 2021 Learning Task Sampling Policy for Multitask Learning EMNLP 2021 Learning to Ask Conversational Questions by Optimizing Levenshtein Distance ACL 2021 Learning to Count via Unbalanced Optimal Transport AAAI 2021 Learning to Defend by Learning to Attack AISTATS 2021 Learning to delegate for large-scale vehicle routing NeurIPS 2021 Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer NeurIPS 2021 Learning to Price Against a Moving Target ICML 2021 Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model AISTATS 2021 Learning To Scale Mixed-Integer Programs AAAI 2021 Learning to Stop with Surprisingly Few Samples COLT 2021 Learning to Switch Optimizers for Quadratic Programming ACML 2021 Learning Treatment Effects in Panels with General Intervention Patterns NeurIPS 2021 Learning User Preferences in Non-Stationary Environments AISTATS 2021 Learning View Selection for 3D Scenes CVPR 2021 Learning with Gradient Descent and Weakly Convex Losses AISTATS 2021 Learning With Privileged Tasks ICCV 2021 Learning with risk-averse feedback under potentially heavy tails AISTATS 2021 Learning with semi-definite programming: statistical bounds based on fixed point analysis and excess risk curvature JMLR 2021 Learn The Big Picture: Representation Learning for Clustering ACL 2021 LEO: Learning Energy-based Models in Factor Graph Optimization CoRL 2021 Leveraging Non-uniformity in First-order Non-convex Optimization ICML 2021 Lifelong Learning with Sketched Structural Regularization ACML 2021 Lifelong Multi-Agent Path Finding in Large-Scale Warehouses AAAI 2021 Linear and Kernel Classification in the Streaming Model: Improved Bounds for Heavy Hitters NeurIPS 2021