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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)

Private Query Release Assisted by Public Data ICML 2020 Probabilistic Assumptions Matter: Improved Models for Distantly-Supervised Document-Level Question Answering ACL 2020 Probabilistic Circuits for Variational Inference in Discrete Graphical Models NeurIPS 2020 Probabilistic Connection Importance Inference and Lossless Compression of Deep Neural Networks ICLR 2020 Probabilistic Extension of Precision, Recall, and F1 Score for More Thorough Evaluation of Classification Models EMNLP 2020 Probabilistic Inference for Predicate Constraint Satisfaction AAAI 2020 Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations NeurIPS 2020 Probabilistic Linear Solvers for Machine Learning NeurIPS 2020 Probabilistic Pixel-Adaptive Refinement Networks CVPR 2020 Probabilistic Regression for Visual Tracking CVPR 2020 Probabilistic Safety for Bayesian Neural Networks UAI 2020 Probabilistic Super Resolution for Mineral Spectroscopy AAAI 2020 Probabilistic Video Prediction From Noisy Data With a Posterior Confidence CVPR 2020 Probably Approximately Correct Constrained Learning NeurIPS 2020 Probably Approximately Correct Vision-Based Planning using Motion Primitives CoRL 2020 Probing for Multilingual Numerical Understanding in Transformer-Based Language Models EMNLP 2020 Probing Linguistic Features of Sentence-Level Representations in Neural Relation Extraction ACL 2020 Problems with Shapley-value-based explanations as feature importance measures ICML 2020 Production-based Cognitive Models as a Test Suite for Reinforcement Learning Algorithms EMNLP 2020 Profile Entropy: A Fundamental Measure for the Learnability and Compressibility of Distributions NeurIPS 2020 Progressive Boundary Refinement Network for Temporal Action Detection AAAI 2020 Projected Stein Variational Gradient Descent NeurIPS 2020 Projection-Based Constrained Policy Optimization ICLR 2020 Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method NeurIPS 2020 Projection-free Distributed Online Convex Optimization with O(√T) Communication Complexity ICML 2020