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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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Papers (including subtopics)

Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension COLT 2023 Optimal randomized multilevel Monte Carlo for repeatedly nested expectations ICML 2023 Optimal Rates and Efficient Algorithms for Online Bayesian Persuasion ICML 2023 Optimal Rates for Bandit Nonstochastic Control NeurIPS 2023 Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework NeurIPS 2023 Optimal Resource Allocation for Early Stopping-based Neural Architecture Search Methods AutoML 2023 Optimal robustness-consistency tradeoffs for learning-augmented metrical task systems AISTATS 2023 Optimal Sample Complexity Bounds for Non-convex Optimization under Kurdyka-Lojasiewicz Condition AISTATS 2023 Optimal Sets and Solution Paths of ReLU Networks ICML 2023 Optimal Shrinkage for Distributed Second-Order Optimization ICML 2023 Optimal Sparse Regression Trees AAAI 2023 Optimal Strategies for Reject Option Classifiers JMLR 2023 Optimal Time Complexities of Parallel Stochastic Optimization Methods Under a Fixed Computation Model NeurIPS 2023 Optimal Transport for Offline Imitation Learning ICLR 2023 Optimal Transport Model Distributional Robustness NeurIPS 2023 Optimal Treatment Allocation for Efficient Policy Evaluation in Sequential Decision Making NeurIPS 2023 Optimism and Delays in Episodic Reinforcement Learning AISTATS 2023 Optimism in Face of a Context:Regret Guarantees for Stochastic Contextual MDP AAAI 2023 Optimistic Exploration with Learned Features Provably Solves Markov Decision Processes with Neural Dynamics ICLR 2023 Optimistic Meta-Gradients NeurIPS 2023 Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization ICML 2023 Optimistic Planning by Regularized Dynamic Programming ICML 2023 Optimistic Rates for Multi-Task Representation Learning NeurIPS 2023 Optimistic Thompson Sampling-based algorithms for episodic reinforcement learning UAI 2023 Optimization and Bayes: A Trade-off for Overparameterized Neural Networks NeurIPS 2023