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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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828
3,646
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2000
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Papers (including subtopics)

Forest vs Tree: The (N, K) Trade-off in Reproducible ML Evaluation AAAI 2026 ForeSWE: Forecasting Snow-Water Equivalent with an Uncertainty-Aware Attention Model AAAI 2026 Formalizing Task-Space Complexity for Zero-Shot Generalization L4DC 2026 Formal Verification of Neural ODE for Safety Evaluation in Autonomous Vehicles AAAI 2026 Fourier Weak SINDy: Spectral Test Function Selection for Robust Model Identification L4DC 2026 FP=XINT: Representing Neural Networks via Low-Bit Series Basis Functions AAAI 2026 FreLay: Frequency-aware Energy Function for Training-free Layout-to-Image Generation AAAI 2026 FreqCycle: A Multi-Scale Time-Frequency Analysis Method for Time Series Forecasting AAAI 2026 Frequency-Dependent Scheduled Schrödinger Bridge for Underwater Acoustic Signal Denoising AAAI 2026 Frequency Is What You Need: Considering Word Frequency When Text Masking Benefits Vision-Language Model Pre-training WACV 2026 From Continual Learning to SGD and Back: Better Rates for Continual Linear Models ALT 2026 From Hypothesis to Premises: LLM-based Backward Logical Reasoning with Selective Symbolic Translation AAAI 2026 From Intent to Execution: Multimodal Chain-of-Thought Reinforcement Learning for Precise CAD Code Generation AAAI 2026 From Mathematical Reasoning to Code: Generalization of Process Reward Models in Test-Time Scaling AAAI 2026 From Parameter to Representation: A Closed-Form Approach for Controllable Model Merging AAAI 2026 From Sequential to Recursive: Enhancing Decision-Focused Learning with Bidirectional Feedback AAAI 2026 FT-NCFM: An Influence-Aware Data Distillation Framework for Efficient VLA Models AAAI 2026 Full-Atom Peptide Design via Riemannian–Euclidean Bayesian Flow Networks AAAI 2026 Functional Stochastic Localization COLT 2026 Function-on-Function Bayesian Optimization AAAI 2026 FusedRec: Fused Embedding Communication for Distributed Recommendation Training on GPUs AAAI 2026 FUSION: Dataset Pruning via Fusing Uncertainty with Structural Information for Optimal Neural Training in Crystal Property Prediction AAAI 2026 GAHMN: A Generative Approach for High-Dimensional Mediation Analysis AAAI 2026 Garbage In, Reasoning Out? Why Benchmark Scores are Unreliable and What to Do About It EACL 2026 GAST: Gradient-aligned Sparse Tuning of Large Language Models with Data-layer Selection EACL 2026