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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)

A dynamic model of lexical experience for tracking of oral reading fluency ACL 2023 A Fair Generative Model Using LeCam Divergence AAAI 2023 A Fast Adaptive Randomized PCA Algorithm IJCAI 2023 A Fast and Accurate Estimator for Large Scale Linear Model via Data Averaging NeurIPS 2023 A Fast Optimistic Method for Monotone Variational Inequalities ICML 2023 A Fast, Well-Founded Approximation to the Empirical Neural Tangent Kernel ICML 2023 A Finite-Particle Convergence Rate for Stein Variational Gradient Descent NeurIPS 2023 A finite-sample analysis of multi-step temporal difference estimates L4DC 2023 A Finite Sample Complexity Bound for Distributionally Robust Q-learning AISTATS 2023 A Flexible Diffusion Model ICML 2023 A Fractional Graph Laplacian Approach to Oversmoothing NeurIPS 2023 A Framework for Adapting Offline Algorithms to Solve Combinatorial Multi-Armed Bandit Problems with Bandit Feedback ICML 2023 A Fully First-Order Method for Stochastic Bilevel Optimization ICML 2023 A future for universal grapheme-phoneme transduction modeling with neuralized finite-state transducers ACL 2023 AGAIN: Adversarial Training With Attribution Span Enlargement and Hybrid Feature Fusion CVPR 2023 AGD: an Auto-switchable Optimizer using Stepwise Gradient Difference for Preconditioning Matrix NeurIPS 2023 A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis ICLR 2023 A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning ICLR 2023 A Generalizable Physics-informed Learning Framework for Risk Probability Estimation L4DC 2023 A Generalized Unbiased Risk Estimator for Learning with Augmented Classes AAAI 2023 A General Regret Bound of Preconditioned Gradient Method for DNN Training CVPR 2023 A General Representation Learning Framework with Generalization Performance Guarantees ICML 2023 A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates JMLR 2023 A General Theory of Correct, Incorrect, and Extrinsic Equivariance NeurIPS 2023 A Generation-based Deductive Method for Math Word Problems EMNLP 2023