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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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'25

Papers (including subtopics)

Steepest Descent Density Control for Compact 3D Gaussian Splatting CVPR 2025 Steering Knowledge Selection Behaviours in LLMs via SAE-Based Representation Engineering NAACL 2025 Steering Large Language Models between Code Execution and Textual Reasoning ICLR 2025 Steering off Course: Reliability Challenges in Steering Language Models ACL 2025 Steering Protein Family Design through Profile Bayesian Flow ICLR 2025 Steering Protein Language Models ICML 2025 SteerX: Creating Any Camera-Free 3D and 4D Scenes with Geometric Steering ICCV 2025 Step-DAD: Semi-Amortized Policy-Based Bayesian Experimental Design ICML 2025 Step Guided Reasoning: Improving Mathematical Reasoning using Guidance Generation and Step Reasoning EMNLP 2025 Step-KTO: Optimizing Mathematical Reasoning through Stepwise Binary Feedback EMNLP 2025 STEPS: Sequential Probability Tensor Estimation for Text-to-Image Hard Prompt Search CVPR 2025 Stepwise Informativeness Search for Improving LLM Reasoning EMNLP 2025 Stepwise Perplexity-Guided Refinement for Efficient Chain-of-Thought Reasoning in Large Language Models ACL 2025 Stepwise Reasoning Checkpoint Analysis: A Test Time Scaling Method to Enhance LLMs’ Reasoning EMNLP 2025 S*: Test Time Scaling for Code Generation EMNLP 2025 STIMULUS: Achieving Fast Convergence and Low Sample Complexity in Stochastic Multi-Objective Learning UAI 2025 StitchLLM: Serving LLMs, One Block at a Time ACL 2025 Stochastic Approximation with Unbounded Markovian Noise: A General-Purpose Theorem AISTATS 2025 Stochastic Bandits Robust to Adversarial Attacks ICLR 2025 Stochastic Chameleons: Irrelevant Context Hallucinations Reveal Class-Based (Mis)Generalization in LLMs ACL 2025 Stochastic Compositional Minimax Optimization with Provable Convergence Guarantees AISTATS 2025 Stochastic Control for Fine-tuning Diffusion Models: Optimality, Regularity, and Convergence ICML 2025 Stochastic Deep Restoration Priors for Imaging Inverse Problems ICML 2025 Stochastic Forward–Backward Deconvolution: Training Diffusion Models with Finite Noisy Datasets ICML 2025 Stochastic Gradient Estimation for Higher-Order Differentiable Rendering ICCV 2025