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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)

Revisiting Learning Rate Control AutoML 2025 Revisiting LocalSGD and SCAFFOLD: Improved Rates and Missing Analysis AISTATS 2025 Revisiting Mode Connectivity in Neural Networks with Bezier Surface ICLR 2025 Revisiting Neural Networks for Few-Shot Learning: A Zero-Cost NAS Perspective ICML 2025 Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel–Young Loss Perspective and Gap-Dependent Regret Analysis AISTATS 2025 Revisiting Prefix-tuning: Statistical Benefits of Reparameterization among Prompts ICLR 2025 Revisiting Projection-Free Online Learning with Time-Varying Constraints AAAI 2025 Revisiting Scaling Laws for Language Models: The Role of Data Quality and Training Strategies ACL 2025 Revisiting Self-Consistency from Dynamic Distributional Alignment Perspective on Answer Aggregation ACL 2025 Revisiting Source-Free Domain Adaptation: a New Perspective via Uncertainty Control ICLR 2025 Revisiting the Berkeley Admissions data: Statistical Tests for Causal Hypotheses UAI 2025 Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling Capabilities? ACL 2025 Revisiting Unbiased Implicit Variational Inference ICML 2025 Revisiting Uncertainty Quantification Evaluation in Language Models: Spurious Interactions with Response Length Bias Results ACL 2025 Revisiting Weak-to-Strong Generalization in Theory and Practice: Reverse KL vs. Forward KL ACL 2025 Revisiting Zeroth-Order Optimization: Minimum-Variance Two-Point Estimators and Directionally Aligned Perturbations ICLR 2025 Revisit Micro-batch Clipping: Adaptive Data Pruning via Gradient Manipulation ICLR 2025 Revitalizing Saturated Benchmarks: A Weighted Metric Approach for Differentiating Large Language Model Performance NAACL 2025 REVIVING YOUR MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing EMNLP 2025 Revolve: Optimizing AI Systems by Tracking Response Evolution in Textual Optimization ICML 2025 REvolve: Reward Evolution with Large Language Models using Human Feedback ICLR 2025 REVS: Unlearning Sensitive Information in Language Models via Rank Editing in the Vocabulary Space ACL 2025 Reward-Augmented Data Enhances Direct Preference Alignment of LLMs ICML 2025 RewardDS: Privacy-Preserving Fine-Tuning for Large Language Models via Reward Driven Data Synthesis EMNLP 2025 Reward Fine-Tuning Two-Step Diffusion Models via Learning Differentiable Latent-Space Surrogate Reward CVPR 2025