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Optimization & Theory

43,292 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

1
52
352
828
3,646
5,854
2000
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'25

Papers (including subtopics)

Learning to Learn to be Right for the Right Reasons NAACL 2021 Learning to Plan Optimistically: Uncertainty-Guided Deep Exploration via Latent Model Ensembles CoRL 2021 Learning to Predict Trustworthiness with Steep Slope Loss 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 Select Exogenous Events for Marked Temporal Point Process NeurIPS 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 Whenever Learning is Possible: Universal Learning under General Stochastic Processes JMLR 2021 Learning with Generated Teammates to Achieve Type-Free Ad-Hoc Teamwork IJCAI 2021 Learning with Gradient Descent and Weakly Convex Losses AISTATS 2021 Learning with Hyperspherical Uniformity AISTATS 2021 Learning Within an Instance for Designing High-Revenue Combinatorial Auctions IJCAI 2021 Learning with invariances in random features and kernel models COLT 2021 Learning With Privileged Tasks ICCV 2021 Learning with Retrospection AAAI 2021 Learning with risk-averse feedback under potentially heavy tails AISTATS 2021 Learning with Safety Constraints: Sample Complexity of Reinforcement Learning for Constrained MDPs AAAI 2021 Learning with semi-definite programming: statistical bounds based on fixed point analysis and excess risk curvature JMLR 2021 Learning with User-Level Privacy NeurIPS 2021 Learn The Big Picture: Representation Learning for Clustering ACL 2021