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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)

Dissecting Lottery Ticket Transformers: Structural and Behavioral Study of Sparse Neural Machine Translation EMNLP 2020 Dissecting Neural ODEs NeurIPS 2020 Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation ICML 2020 Dissecting Span Identification Tasks with Performance Prediction EMNLP 2020 Distance-Based Equilibria in Normal-Form Games AAAI 2020 Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression AAAI 2020 Distortion estimates for approximate Bayesian inference UAI 2020 DIST: Rendering Deep Implicit Signed Distance Function With Differentiable Sphere Tracing CVPR 2020 Distributed Bandit Learning: Near-Optimal Regret with Efficient Communication ICLR 2020 Distributed Distillation for On-Device Learning NeurIPS 2020 Distributed Feature Screening via Componentwise Debiasing JMLR 2020 Distributed High-dimensional Regression Under a Quantile Loss Function JMLR 2020 Distributed Kernel Ridge Regression with Communications JMLR 2020 Distributed Machine Learning through Heterogeneous Edge Systems AAAI 2020 Distributed Minimum Error Entropy Algorithms JMLR 2020 Distributed Newton Can Communicate Less and Resist Byzantine Workers NeurIPS 2020 Distributed Online Optimization over a Heterogeneous Network with Any-Batch Mirror Descent ICML 2020 Distributed, partially collapsed MCMC for Bayesian Nonparametrics AISTATS 2020 Distributed Primal-Dual Optimization for Online Multi-Task Learning AAAI 2020 Distributed Signal Detection under Communication Constraints COLT 2020 Distributed Stochastic Gradient Descent with Event-Triggered Communication AAAI 2020 Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based Algorithms NeurIPS 2020 Distributionally Ambiguous Optimization for Batch Bayesian Optimization JMLR 2020 Distributionally Robust Bayesian Optimization AISTATS 2020 Distributionally Robust Bayesian Quadrature Optimization AISTATS 2020