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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)

Integral-based Knockoffs Inference for Partially Linear Models AAAI 2026 Integrating Reweighted Least Squares with Plug-and-Play Diffusion Priors for Noisy Image Restoration AAAI 2026 Interest-Shift-Aware Logical Reasoning for Efficient Long-Sequence Recommendation AAAI 2026 Intermediate N-Gramming: Deterministic and Fast N-Grams for Large N and Large Datasets AAAI 2026 InterMoE: Individual-Specific 3D Human Interaction Generation via Dynamic Temporal-Selective MoE AAAI 2026 Interpolated Stochastic Interventions Based on Propensity Scores, Target Policies and Treatment-Specific Costs AAAI 2026 Interpreting Capsule Networks for Image Classification by Routing Path Visualization (Abstract Reprint) AAAI 2026 Interpreting Fedspeak with Confidence: A LLM-Based Uncertainty-Aware Framework Guided by Monetary Policy Transmission Paths AAAI 2026 Intra-Class Probabilistic Embeddings for Uncertainty Estimation in Vision-Language Models WACV 2026 Investigating Social Bias Propagation in Federated Fine-tuning of Large Language Models AAAI 2026 Invited Open Problem: Does Differential Privacy Make PAC Learning Much Harder? COLT 2026 Invited Open Problem: Is the Power of Deep Learning over Linear Models Inherently Distribution Dependent? COLT 2026 Invited Open Problem: Online Optimization of Piecewise-Lipschitz Functions with Applications to Data-Driven Algorithm Design COLT 2026 IROTE: Human-like Traits Elicitation of Large Language Model via In-Context Self-Reflective Optimization AAAI 2026 IRPO: Implicit Policy Regularized Preference Optimization EACL 2026 Is Memorization Helpful or Harmful? Prior Information Sets the Threshold COLT 2026 Is Multi-Distribution Learning as Easy as PAC Learning: Sharp Rates with Bounded Label Noise COLT 2026 Iterative Structured Pruning for Large Language Models with Multi-Domain Calibration EACL 2026 Jailbreaks as Inference-Time Alignment: A Framework for Understanding Safety Failures in LLMs EACL 2026 JOCA: Task-Driven Joint Optimisation of Camera Hardware and Adaptive Camera Control Algorithms WACV 2026 Joint Modeling of Corruption-Driven and Information-Limited Uncertainty for Robust 3D Gaussian Splatting WACV 2026 Joint Multimodal Preference Optimization for Fine-Grained Visual-Textual Alignment EACL 2026 Joint Optimization of Camera Model and Deep Neural Network for Image Recognition WACV 2026 Jupiter: Enhancing LLM Data Analysis Capabilities via Notebook and Inference-Time Value-Guided Search AAAI 2026 Just Few States Are Enough: Randomized Sparse Feedback for Stability of Dynamical Systems AAAI 2026