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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

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52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Regret Bounds for Online Kernel Selection in Continuous Kernel Space AAAI 2021 Regret Minimization Experience Replay in Off-Policy Reinforcement Learning NeurIPS 2021 Regret Minimization in Heavy-Tailed Bandits COLT 2021 Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient Approach ICML 2021 Regret-Optimal Filtering AISTATS 2021 Regret-optimal measurement-feedback control L4DC 2021 Regularising Fisher Information Improves Cross-lingual Generalisation EMNLP 2021 Regularization in ResNet with Stochastic Depth NeurIPS 2021 Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network AISTATS 2021 Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control ICLR 2021 Regularization Strategy for Point Cloud via Rigidly Mixed Sample CVPR 2021 Regularized ERM on random subspaces AISTATS 2021 Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and Beyond NeurIPS 2021 Regularized Policies are Reward Robust AISTATS 2021 Regularizing Neural Networks via Adversarial Model Perturbation CVPR 2021 Regularizing towards Causal Invariance: Linear Models with Proxies ICML 2021 Regulating Greed Over Time in Multi-Armed Bandits JMLR 2021 Reinforced Few-Shot Acquisition Function Learning for Bayesian Optimization NeurIPS 2021 Reinforced Multi-Teacher Selection for Knowledge Distillation AAAI 2021 Reinforcement Learning based Disease Progression Model for Alzheimer’s Disease NeurIPS 2021 Reinforcement Learning for Abstractive Question Summarization with Question-aware Semantic Rewards ACL 2021 Reinforcement Learning for Cost-Aware Markov Decision Processes ICML 2021 Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection NeurIPS 2021 Reinforcement Learning in Newcomblike Environments NeurIPS 2021 Reinforcement Learning in Parametric MDPs with Exponential Families AISTATS 2021