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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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Papers (including subtopics)

On Pairwise Quantile Regression - Statistical Guarantees and Applications UAI 2026 On Randomized Algorithms in Online Strategic Classification COLT 2026 On Robustness of Linear Classifiers to Targeted Data Poisoning AAAI 2026 On the Asymptotics of Self-Supervised Pre-training: Two-Stage M-Estimation and Representation Symmetry COLT 2026 On The Complexity of Best-Arm Identification in Non-Stationary Linear Bandits COLT 2026 On the Computational Tractability of Probabilistic Global and Local Sufficient Explanation AAAI 2026 On the Convergence of Overparameterized Problems: Inherent Properties of the Compositional Structure of Neural Networks L4DC 2026 On the Dataless Training of Neural Networks AAAI 2026 On the Evaluation of Capability Estimation Methods for Large Language Models AAAI 2026 On the Exponential Convergence for Offline RLHF with Pairwise Comparisons AAAI 2026 On the Gradient Complexity of Private Optimization with Private Oracles COLT 2026 On the Hardness of Learning Regular Expressions ALT 2026 On the Hidden Objective Biases of Group-based Reinforcement Learning ACL 2026 On the Importance of Randomization in Discriminative Feature Feedback COLT 2026 On the Information Processing of One-Dimensional Wasserstein Distances with Finite Samples AAAI 2026 On the Interplay between Human Label Variation and Model Fairness EACL 2026 On the Learning Dynamics of Two-layer Linear Networks with Label Noise SGD AAAI 2026 On the Misalignment Between Data Learnability and Forgettability in Machine Unlearning AAAI 2026 On the Probabilistic Learnability of Compact Neural Network Preimage Bounds AAAI 2026 On the Robustness of Bandit Multiple Testing AAAI 2026 On the Stability of Nonlinear Dynamics in GD and SGD: Beyond Quadratic Potentials COLT 2026 On the Statistical Query Complexity of Learning Semiautomata: a Random Walk Approach COLT 2026 On the Sublinear Regret of Continuous K-Max Bandits UAI 2026 On the Superimposed Noise Accumulation Problem in Sequential Knowledge Editing of Large Language Models AAAI 2026 Open Problem: Is Interaction Necessary for Order-Optimal 1-bit Mean Estimation? COLT 2026