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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

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52
352
828
3,646
5,854
2000
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Papers (including subtopics)

AdaR: An Adaptive Gradient Method with Cyclical Restarting of Moment Estimations IJCAI 2025 AdaRankGrad: Adaptive Gradient Rank and Moments for Memory-Efficient LLMs Training and Fine-Tuning ICLR 2025 AdaRewriter: Unleashing the Power of Prompting-based Conversational Query Reformulation via Test-Time Adaptation EMNLP 2025 AdaSkip: Adaptive Sublayer Skipping for Accelerating Long-Context LLM Inference AAAI 2025 A Datalog Rewriting Algorithm for Warded Ontologies IJCAI 2025 AdaV: Adaptive Text-visual Redirection for Vision-Language Models ACL 2025 ADBA: Approximation Decision Boundary Approach for Black-Box Adversarial Attacks AAAI 2025 Addax: Utilizing Zeroth-Order Gradients to Improve Memory Efficiency and Performance of SGD for Fine-Tuning Language Models ICLR 2025 Additive Model Boosting: New Insights and Path(ologie)s AISTATS 2025 Add-One-In: Incremental Sample Selection for Large Language Models via a Choice-Based Greedy Paradigm EMNLP 2025 ADDQ: Adaptive distributional double Q-learning ICML 2025 Addressing Concept Mislabeling in Concept Bottleneck Models Through Preference Optimization ICML 2025 Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts ICML 2025 Addressing Misspecification in Simulation-based Inference through Data-driven Calibration ICML 2025 Addressing the Training-Inference Discrepancy in Discrete Diffusion for Text Generation COLING 2025 A Decentralized Proximal Gradient Tracking Algorithm for Composite Optimization on Riemannian Manifolds JMLR 2025 A Deep Generative Learning Approach for Two-stage Adaptive Robust Optimization ICLR 2025 ADELA: Accelerating Evolutionary Design of Machine Learning Pipelines with the Accompanying Surrogate Model AAAI 2025 ADFormer: Aggregation Differential Transformer for Passenger Demand Forecasting IJCAI 2025 ADHMR: Aligning Diffusion-based Human Mesh Recovery via Direct Preference Optimization ICML 2025 A Differentiable Rank-Based Objective for Better Feature Learning ICLR 2025 A Differentiable Wave Optics Model for End-to-End Computational Imaging System Optimization ICCV 2025 A Differential Inclusion Approach for Learning Heterogeneous Sparsity in Neuroimaging Analysis AISTATS 2025 A Distributional Approach to Uncertainty-Aware Preference Alignment Using Offline Demonstrations ICLR 2025 A Distributional-Lifting Theorem for PAC Learning COLT 2025