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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)

Learning Best Combination for Efficient N:M Sparsity NeurIPS 2022 Learning Bounded Context-Free-Grammar via LSTM and the Transformer: Difference and the Explanations AAAI 2022 Learning by Directional Gradient Descent ICLR 2022 Learning Causal Models from Conditional Moment Restrictions by Importance Weighting ICLR 2022 Learning Chaotic Dynamics in Dissipative Systems NeurIPS 2022 Learning Cluster Causal Diagrams: An Information-Theoretic Approach IJCAI 2022 Learning Competitive Equilibria in Exchange Economies with Bandit Feedback AISTATS 2022 Learning Continuous Graph Structure with Bilevel Programming for Graph Neural Networks IJCAI 2022 Learning Cross-Task Dependencies for Joint Extraction of Entities, Events, Event Arguments, and Relations EMNLP 2022 Learning curves for continual learning in neural networks: Self-knowledge transfer and forgetting ICLR 2022 Learning Curves for Gaussian Process Regression with Power-Law Priors and Targets ICLR 2022 Learning Curves for SGD on Structured Features ICLR 2022 Learning Deep Input-Output Stable Dynamics NeurIPS 2022 Learning Degradation Uncertainty for Unsupervised Real-world Image Super-resolution IJCAI 2022 Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval (Extended Abstract) IJCAI 2022 Learning Discrete Structured Variational Auto-Encoder using Natural Evolution Strategies ICLR 2022 Learning Disentangled Representations of Negation and Uncertainty ACL 2022 Learning Distributed Channel Access Policies for Networked Estimation: Data-driven Optimization in the Mean-field Regime L4DC 2022 Learning Distributionally Robust Models at Scale via Composite Optimization ICLR 2022 Learning Distributions Generated by Single-Layer ReLU Networks in the Presence of Arbitrary Outliers NeurIPS 2022 Learning Diverse and Physically Feasible Dexterous Grasps with Generative Model and Bilevel Optimization CoRL 2022 Learning Domain Adaptive Object Detection with Probabilistic Teacher ICML 2022 Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces NeurIPS 2022 Learning dynamics of deep linear networks with multiple pathways NeurIPS 2022 Learning Efficient and Robust Ordinary Differential Equations via Invertible Neural Networks ICML 2022