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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)

Improve Safety Training of Large Language Models with Safety-Critical Singular Vectors Localization ACL 2025 Improving Accuracy and Calibration via Differentiated Deep Mutual Learning CVPR 2025 Improving Accuracy of Low-resource ASR using Rule-Based Character Constituency Loss (RBCCL) COLING 2025 Improving Causal Interventions in Amnesic Probing with Mean Projection or LEACE ACL 2025 Improving Contextual Faithfulness of Large Language Models via Retrieval Heads-Induced Optimization ACL 2025 Improving Continual Pre-training Through Seamless Data Packing ACL 2025 Improving Convergence Guarantees of Random Subspace Second-order Algorithm for Nonconvex Optimization ICLR 2025 Improving Cooperation in Language Games with Bayesian Inference and the Cognitive Hierarchy AAAI 2025 Improving Deep Detector Robustness via Detection-Related Discriminant Maximization and Reorganization WACV 2025 Improving Deep Learning Speed and Performance Through Synaptic Neural Balance AAAI 2025 Improving Deep Regression with Tightness ICLR 2025 Improving Diffusion Inverse Problem Solving with Decoupled Noise Annealing CVPR 2025 Improving Diversity in Language Models: When Temperature Fails, Change the Loss ICML 2025 Improving Efficiency of Sampling-based Motion Planning via Message-Passing Monte Carlo CoRL 2025 Improving Federated Domain Generalization Through Dynamical Weights Calculated from Data Influences on Global Model Update AAAI 2025 Improving Flow Matching by Aligning Flow Divergence ICML 2025 Improving Generalization in Federated Learning with Highly Heterogeneous Data via Momentum-Based Stochastic Controlled Weight Averaging ICML 2025 Improving Generalization in Meta-Learning via Meta-Gradient Augmentation IJCAI 2025 Improving Generalization of Deep Neural Networks by Optimum Shifting AAAI 2025 Improving Generalization of Universal Adversarial Perturbation via Dynamic Maximin Optimization AAAI 2025 Improving Generalization with Flat Hilbert Bayesian Inference ICML 2025 Improving LLM Safety Alignment with Dual-Objective Optimization ICML 2025 Improving Model Probability Calibration by Integration of Large Data Sources with Biased Labels AAAI 2025 Improving Multimodal Learning via Imbalanced Learning ICCV 2025 Improving Neural Optimal Transport via Displacement Interpolation ICLR 2025