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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
'5
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'20
'25

Papers (including subtopics)

Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference ICLR 2025 Enabling Silent Telemetry Data Transmission with InvisiFlow NSDI 2025 End-to-End Learning Framework for Solving Non-Markovian Optimal Control ICML 2025 End-to-end Learning of Gaussian Mixture Priors for Diffusion Sampler ICLR 2025 End-to-End Optimization for Multimodal Retrieval-Augmented Generation via Reward Backpropagation EMNLP 2025 Energy-Based Preference Model Offers Better Offline Alignment than the Bradley-Terry Preference Model ICML 2025 Energy Considerations of Large Language Model Inference and Efficiency Optimizations ACL 2025 Energy-Weighted Flow Matching for Offline Reinforcement Learning ICLR 2025 Enforcing Idempotency in Neural Networks ICML 2025 Enhanced H-Consistency Bounds ALT 2025 Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization AISTATS 2025 Enhanced Equilibria-Solving via Private Information Pre-Branch Structure in Adversarial Team Games UAI 2025 Enhanced Feature Learning via Regularisation: Integrating Neural Networks and Kernel Methods JMLR 2025 Enhanced Importance Sampling Through Latent Space Exploration in Normalizing Flows AAAI 2025 Enhanced Sample Selection with Confidence Tracking: Identifying Correctly Labeled Yet Hard-to-Learn Samples in Noisy Data AAAI 2025 Enhancing Adversarial Robustness with Conformal Prediction: A Framework for Guaranteed Model Reliability ICML 2025 Enhancing Adversarial Transferability by Balancing Exploration and Exploitation with Gradient-Guided Sampling ICCV 2025 Enhancing Adversarial Transferability with Adversarial Weight Tuning AAAI 2025 Enhancing Certified Robustness via Block Reflector Orthogonal Layers and Logit Annealing Loss ICML 2025 Enhancing Chain-of-Thought Reasoning with Critical Representation Fine-tuning ACL 2025 Enhancing Decision Making Through the Integration of Large Language Models and Operations Research Optimization AAAI 2025 Enhancing Diversity In Parallel Agents: A Maximum State Entropy Exploration Story ICML 2025 Enhancing Efficiency and Exploration in Reinforcement Learning for LLMs EMNLP 2025 Enhancing Feature-Specific Data Protection via Bayesian Coordinate Differential Privacy AISTATS 2025 Enhancing Implicit Neural Representations via Symmetric Power Transformation AAAI 2025