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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)

Provable Mutual Benefits from Federated Learning in Privacy-Sensitive Domains AISTATS 2024 Provable Partially Observable Reinforcement Learning with Privileged Information NeurIPS 2024 Provable Policy Gradient Methods for Average-Reward Markov Potential Games AISTATS 2024 Provable Posterior Sampling with Denoising Oracles via Tilted Transport NeurIPS 2024 Provable Privacy with Non-Private Pre-Processing ICML 2024 Provable Reward-Agnostic Preference-Based Reinforcement Learning ICLR 2024 Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation ICML 2024 Provable Robustness against a Union of L_0 Adversarial Attacks AAAI 2024 Provable Tempered Overfitting of Minimal Nets and Typical Nets NeurIPS 2024 Provably and Practically Efficient Adversarial Imitation Learning with General Function Approximation NeurIPS 2024 Provably Better Explanations with Optimized Aggregation of Feature Attributions ICML 2024 Provably Convergent Federated Trilevel Learning AAAI 2024 Provably Efficient CVaR RL in Low-rank MDPs ICLR 2024 Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret ICML 2024 Provably Efficient Interactive-Grounded Learning with Personalized Reward NeurIPS 2024 Provably Efficient Partially Observable Risk-sensitive Reinforcement Learning with Hindsight Observation ICML 2024 Provably Efficient Reinforcement Learning for Adversarial Restless Multi-Armed Bandits with Unknown Transitions and Bandit Feedback ICML 2024 Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation NeurIPS 2024 Provably Efficient UCB-type Algorithms For Learning Predictive State Representations ICLR 2024 Provably Faster Algorithms for Bilevel Optimization via Without-Replacement Sampling NeurIPS 2024 Provably Neural Active Learning Succeeds via Prioritizing Perplexing Samples ICML 2024 Provably Optimal Memory Capacity for Modern Hopfield Models: Transformer-Compatible Dense Associative Memories as Spherical Codes NeurIPS 2024 Provably Robust Conformal Prediction with Improved Efficiency ICLR 2024 Provably Robust DPO: Aligning Language Models with Noisy Feedback ICML 2024 Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction NeurIPS 2024