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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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2000
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Papers (including subtopics)

Lost in Benchmarks? Rethinking Large Language Model Benchmarking with Item Response Theory AAAI 2026 Low-Degree Method Fails to Predict Robust Subspace Recovery COLT 2026 Low-Rank Curvature for Zeroth-Order Optimization in LLM Fine-tuning AAAI 2026 LPPG-RL: Lexicographically Projected Policy Gradient Reinforcement Learning with Subproblem Exploration AAAI 2026 LR-AdaInSeg:Adaptive Instance Segmentation of Incomplete 3D Scenes Driven by Low-Rank Networks AAAI 2026 Lyapunov-Based Sample Complexity Analysis for Weakly-Coupled MDPs (extended abstract) COLT 2026 M2FMoE: Multi-Resolution Multi-View Frequency Mixture-of-Experts for Extreme-Adaptive Time Series Forecasting AAAI 2026 Maastricht University at AMIYA: Adapting LLMs for Dialectal Arabic using Fine-tuning and MBR Decoding EACL 2026 MAJIC: Markovian Adaptive Jailbreaking via Iterative Composition of Diverse Innovative Strategies AAAI 2026 Mapping on a Budget: Optimizing Spatial Data Collection for ML AAAI 2026 Mapping the Course for Prompt-based Structured Prediction EACL 2026 MAPRO: Recasting Multi-Agent Prompt Optimization as Maximum a Posteriori Inference EACL 2026 MAQuA: Multi-outcome Adaptive Question-Asking for Mental Health using Item Response Theory EACL 2026 Marginalized Generalized IoU (MGIoU): A Unified Objective Function for Optimizing Convex Parametric Shapes AAAI 2026 Margin in Abstract Spaces COLT 2026 Markovian Compression: Looking to the Past Helps Accelerate the Future UAI 2026 Marshaled Learning: Bridging Large Neural Networks with Memory-Constrained Trusted Execution Environments in Federated Learning WACV 2026 Martingale Foresight Sampling: A Principled Approach to Inference-Time LLM Decoding EACL 2026 Massively Parallel Proof-Number Search for Impartial Games and Beyond AAAI 2026 Matching Policy Design for Gig Platforms with “Priority” Features AAAI 2026 Matrix-Free Two-to-Infinity and One-to-Two Norms Estimation AAAI 2026 Maximizing Schatten-p Norm Regularization Toward Balance AAAI 2026 MCTS-SQL: Light-Weight LLMs Can Master the Text-to-SQL Through Monte Carlo Tree Search AAAI 2026 MCW-KD: Multi-Cost Wasserstein Knowledge Distillation for Large Language Models AAAI 2026 MDBench: Benchmarking Data-Driven Methods for Model Discovery AAAI 2026