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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)

Risk Bounds of Accelerated SGD for Overparameterized Linear Regression ICLR 2024 Risk-Conditioned Reinforcement Learning: A Generalized Approach for Adapting to Varying Risk Measures AAAI 2024 Risk Estimation in a Markov Cost Process: Lower and Upper Bounds ICML 2024 Risk Measures and Upper Probabilities: Coherence and Stratification JMLR 2024 Risk Seeking Bayesian Optimization under Uncertainty for Obtaining Extremum AISTATS 2024 Risk-sensitive control as inference with Rényi divergence NeurIPS 2024 Risk-Sensitive Policy Optimization via Predictive CVaR Policy Gradient ICML 2024 Risk-Sensitive Reward-Free Reinforcement Learning with CVaR ICML 2024 RL in Latent MDPs is Tractable: Online Guarantees via Off-Policy Evaluation NeurIPS 2024 RLOP: A Framework for Reinforcement Learning, Optimization and Planning Algorithms IJCAI 2024 RL-SeqISP: Reinforcement Learning-Based Sequential Optimization for Image Signal Processing AAAI 2024 RLVF: Learning from Verbal Feedback without Overgeneralization ICML 2024 Robust Active Measuring under Model Uncertainty AAAI 2024 Robust agents learn causal world models ICLR 2024 Robust and Faster Zeroth-Order Minimax Optimization: Complexity and Applications NeurIPS 2024 Robust Angular Synchronization via Directed Graph Neural Networks ICLR 2024 Robust Approximate Sampling via Stochastic Gradient Barker Dynamics AISTATS 2024 Robust Black-Box Optimization for Stochastic Search and Episodic Reinforcement Learning JMLR 2024 Robust Conformal Prediction Using Privileged Information NeurIPS 2024 Robust Data Clustering with Outliers via Transformed Tensor Low-Rank Representation AISTATS 2024 Robust Data-driven Prescriptiveness Optimization ICML 2024 Robust Distributed Gradient Aggregation Using Projections onto Gradient Manifolds AAAI 2024 Robust Distribution Learning with Local and Global Adversarial Corruptions (extended abstract) COLT 2024 Robust Evaluation Measures for Evaluating Social Biases in Masked Language Models AAAI 2024 Robust Gaussian Processes via Relevance Pursuit NeurIPS 2024