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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)

Energy-based Autoregressive Generation for Neural Population Dynamics AAAI 2026 Enhanced Privacy Leakage from Noise-Perturbed Gradients via Gradient-Guided Conditional Diffusion Models AAAI 2026 Enhancing Auto-regressive Chain-of-Thought through Loop-Aligned Reasoning EACL 2026 Enhancing DPSGD via Per-Sample Momentum and Low-Pass Filtering AAAI 2026 Enhancing Exploration and Exploitation in Hierarchical Reinforcement Learning with Subgoal Graph Learning AAAI 2026 Enhancing Interpretability for Vision Models via Shapley Value Optimization AAAI 2026 Enhancing Kernel Power K-means: Scalable and Robust Clustering with Random Fourier Features and Possibilistic Method AAAI 2026 Enhancing Pre-training Data Detection in LLMs Through Discriminative and Symmetric Prefix Selection AAAI 2026 Enhancing Robustness of Offline Reinforcement Learning Under Data Corruption via Sharpness-Aware Minimization (Student Abstract) AAAI 2026 Enjoying Non-linearity in Multinomial Logistic Bandits: A Minimax-Optimal Algorithm ALT 2026 Entropy-Gated Branching for Efficient Test-Time Reasoning EACL 2026 EoH-S: Evolution of Heuristic Set Using LLMs for Automated Heuristic Design AAAI 2026 EPO: Diverse and Realistic Protein Ensemble Generation via Energy Preference Optimization AAAI 2026 Equivalence of Coarse and Fine-Grained Models for Learning with Distribution Shift COLT 2026 ERank: Fusing Supervised Fine-Tuning and Reinforcement Learning for Effective and Efficient Text Reranking AAAI 2026 Error Slice Discovery via Manifold Compactness AAAI 2026 Escaping Optimization Stagnation: Taking Steps Beyond Task Arithmetic via Difference Vectors AAAI 2026 Estimating Joint Interventional Distributions from Marginal Interventional Data CLeaR 2026 Estimating Online Influence Needs Causal Modeling! Counterfactual Analysis of Misinformation Engagement on Social Media AAAI 2026 Estimating the True Distribution of Data Collected with Randomized Response AAAI 2026 Estimation and Inference for Causal Explainability CLeaR 2026 Evaluating Adversarial Robustness of Concept Representations in Sparse Autoencoders EACL 2026 Evaluating Text-to-Image and Text-to-Video Synthesis with a Conditional Frechet Distance WACV 2026 Evaluation of "Probabilities of Causation" in Case-Control Studies: Identification and Estimation UAI 2026 Eventually LIL Regret: Almost Sure $\ln\ln T$ Regret for a sub-Gaussian Mixture on Unbounded Data ALT 2026