Skip to content
conftrace_

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
'5
'10
'15
'20
'25

Papers (including subtopics)

Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models ICML 2025 PROM: Pivoted and Regulated Optimization for Multilingual Instruction Learning NAACL 2025 Propagation of Chaos for Mean-Field Langevin Dynamics and its Application to Model Ensemble ICML 2025 Proper losses regret at least 1/2-order JMLR 2025 Proportionally Fair Matching via Randomized Rounding AAAI 2025 ProPose: Probabilistic 3D Human Pose Estimation with Instance-Level Distribution and Normalizing Flow AAAI 2025 Propulsion: Steering LLM with Tiny Fine-Tuning COLING 2025 ProReflow: Progressive Reflow with Decomposed Velocity CVPR 2025 PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial Attacks AAAI 2025 ProSparse: Introducing and Enhancing Intrinsic Activation Sparsity within Large Language Models COLING 2025 Prototype-based Optimal Transport for Out-of-Distribution Detection IJCAI 2025 Provable and Practical Online Learning Rate Adaptation with Hypergradient Descent ICML 2025 Provable Benefit of Random Permutations over Uniform Sampling in Stochastic Coordinate Descent ICML 2025 Provable Complexity Improvement of AdaGrad over SGD: Upper and Lower Bounds in Stochastic Non-Convex Optimization COLT 2025 Provable Convergence Bounds for Hybrid Dynamical Sampling and Optimization ICLR 2025 Provable In-Context Vector Arithmetic via Retrieving Task Concepts ICML 2025 Provable Length Generalization in Sequence Prediction via Spectral Filtering ICML 2025 Provable Maximum Entropy Manifold Exploration via Diffusion Models ICML 2025 Provable Robust Overfitting Mitigation in Wasserstein Distributionally Robust Optimization ICLR 2025 Provable Uncertainty Decomposition via Higher-Order Calibration ICLR 2025 Provable unlearning in topic modeling and downstream tasks ICLR 2025 Provable weak-to-strong generalization via benign overfitting ICLR 2025 Provably Accurate Shapley Value Estimation via Leverage Score Sampling ICLR 2025 Provably Adaptive Average Reward Reinforcement Learning for Metric Spaces UAI 2025 Provably Cost-Sensitive Adversarial Defense via Randomized Smoothing ICML 2025