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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)

Distinguishing fair from unfair compositional generalization tasks EMNLP 2025 Distributed Cascaded Manifold Hashing Network for Compact Image Set Representation IJCAI 2025 Distributed Conformal Prediction via Message Passing ICML 2025 Distributed Event-Based Learning via ADMM ICML 2025 Distributed LLM Serving on Consumer-Grade GPUs by Reconciling Computation and Communication EMNLP 2025 Distributed Nonparametric Estimation: from Sparse to Dense Samples per Terminal ICML 2025 Distributed Retraction-Free and Communication-Efficient Optimization on the Stiefel Manifold ICML 2025 Distributed Speculative Inference (DSI): Speculation Parallelism for Provably Faster Lossless Language Model Inference ICLR 2025 Distributed Stochastic Bilevel Optimization: Improved Complexity and Heterogeneity Analysis JMLR 2025 Distributional Adversarial Loss AISTATS 2025 Distributionally and Adversarially Robust Logistic Regression via Intersecting Wasserstein Balls UAI 2025 Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute Mapping ICML 2025 Distributionally Robust Policy Evaluation and Learning for Continuous Treatment with Observational Data AAAI 2025 Distributionally Robust Policy Learning under Concept Drifts ICML 2025 Distribution-aware Fairness Learning in Medical Image Segmentation From A Control-Theoretic Perspective ICML 2025 Distribution-Aware Online Learning for Urban Spatiotemporal Forecasting on Streaming Data IJCAI 2025 Distribution Backtracking Builds A Faster Convergence Trajectory for Diffusion Distillation ICLR 2025 Distribution Estimation under the Infinity Norm JMLR 2025 Distribution-Free Data Uncertainty for Neural Network Regression ICLR 2025 Distribution Free Tests for Model Selection Based on Maximum Mean Discrepancy with Estimated Parameters JMLR 2025 Distribution-Free Uncertainty Quantification in Mechanical Ventilation Treatment: A Conformal Deep Q-Learning Framework AAAI 2025 Distribution-Specific Agnostic Conditional Classification With Halfspaces ICLR 2025 DistRL: An Asynchronous Distributed Reinforcement Learning Framework for On-Device Control Agent ICLR 2025 Divergence of Neural Tangent Kernel in Classification Problems ICLR 2025 Divergence-Regularized Discounted Aggregation: Equilibrium Finding in Multiplayer Partially Observable Stochastic Games ICLR 2025