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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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'25

Papers (including subtopics)

Learning Rate Schedules in the Presence of Distribution Shift ICML 2023 Learning Rationalizable Equilibria in Multiplayer Games ICLR 2023 Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation ICML 2023 Learning Reliable Logical Rules with SATNet NeurIPS 2023 Learning ReLU networks to high uniform accuracy is intractable ICLR 2023 Learning Revenue Maximization Using Posted Prices for Stochastic Strategic Patient Buyers AAAI 2023 Learning Robust Representations with Information Bottleneck and Memory Network for RGB-D-based Gesture Recognition ICCV 2023 Learning Robust Statistics for Simulation-based Inference under Model Misspecification NeurIPS 2023 Learning Sample Relationship for Exposure Correction CVPR 2023 Learning Second-Order Attentive Context for Efficient Correspondence Pruning AAAI 2023 Learning Small Decision Trees with Large Domain IJCAI 2023 Learning Sparse and Low-Rank Priors for Image Recovery via Iterative Reweighted Least Squares Minimization ICLR 2023 Learning Sparse Graphon Mean Field Games AISTATS 2023 Learning Sparse Group Models Through Boolean Relaxation ICLR 2023 Learning Survival Distribution with Implicit Survival Function IJCAI 2023 Learning the Distribution of Errors in Stereo Matching for Joint Disparity and Uncertainty Estimation CVPR 2023 Learning the dynamics of autonomous nonlinear delay systems L4DC 2023 Learning the Efficient Frontier NeurIPS 2023 Learning the Finer Things: Bayesian Structure Learning at the Instantiation Level AAAI 2023 Learning the Positions in CountSketch ICLR 2023 Learning threshold neurons via edge of stability NeurIPS 2023 Learning to Augment Distributions for Out-of-distribution Detection NeurIPS 2023 Learning to Bid in Repeated First-Price Auctions with Budgets ICML 2023 Learning to Boost Training by Periodic Nowcasting Near Future Weights ICML 2023 Learning to CROSS exchange to solve min-max vehicle routing problems ICLR 2023