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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)

Reward Generalization in RLHF: A Topological Perspective ACL 2025 Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design ICML 2025 Reward-Guided Tree Search for Inference Time Alignment of Large Language Models NAACL 2025 Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning ICLR 2025 Rewarding the Unlikely: Lifting GRPO Beyond Distribution Sharpening EMNLP 2025 Reward Maximization for Pure Exploration: Minimax Optimal Good Arm Identification for Nonparametric Multi-Armed Bandits AISTATS 2025 Reward Modeling with Ordinal Feedback: Wisdom of the Crowd ICML 2025 Reward-Shifted Speculative Sampling Is An Efficient Test-Time Weak-to-Strong Aligner EMNLP 2025 RFMamba: Frequency-Aware State Space Model for RF-Based Human-Centric Perception ICLR 2025 RhythmMamba: Fast, Lightweight, and Accurate Remote Physiological Measurement AAAI 2025 Riemannian Bilevel Optimization JMLR 2025 Riemannian Diffusion Adaptation for Distributed Optimization on Manifolds ICML 2025 Riemannian Geometric-based Meta Learning AAAI 2025 Riemannian-Geometric Fingerprints of Generative Models ICCV 2025 Riemannian Optimization for LoRA on the Stiefel Manifold EMNLP 2025 RiemStega: Covariance-Based Loss for Print-Proof Transmission of Data in Images WACV 2025 Right Now, Wrong Then: Non-Stationary Direct Preference Optimization under Preference Drift ICML 2025 Right Time to Learn: Promoting Generalization via Bio-inspired Spacing Effect in Knowledge Distillation ICML 2025 Ringmaster ASGD: The First Asynchronous SGD with Optimal Time Complexity ICML 2025 RiOT: Efficient Prompt Refinement with Residual Optimization Tree ACL 2025 Risk-averse Total-reward MDPs with ERM and EVaR AAAI 2025 Risk Controlled Image Retrieval AAAI 2025 Risk-sensitive Bandits: Arm Mixture Optimality and Regret-efficient Algorithms AISTATS 2025 Risk-Sensitive Diffusion: Robustly Optimizing Diffusion Models with Noisy Samples ICLR 2025 RIVAL: Reinforcement Learning with Iterative and Adversarial Optimization for Machine Translation EMNLP 2025