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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)

The LOB Recreation Model: Predicting the Limit Order Book from TAQ History Using an Ordinary Differential Equation Recurrent Neural Network AAAI 2021 The Lottery Ticket Hypothesis for Object Recognition CVPR 2021 The Low-Dimensional Linear Geometry of Contextualized Word Representations CoNLL 2021 The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization ICCV 2021 The Minecraft Kernel: Modelling correlated Gaussian Processes in the Fourier domain AISTATS 2021 The Min-Max Complexity of Distributed Stochastic Convex Optimization with Intermittent Communication COLT 2021 The Multiple Instance Learning Gaussian Process Probit Model AISTATS 2021 The neural moving average model for scalable variational inference of state space models UAI 2021 The Neural Tangent Link Between CNN Denoisers and Non-Local Filters CVPR 2021 The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals in the SQ Model COLT 2021 Theoretical Analyses of Multi-Objective Evolutionary Algorithms on Multi-Modal Objectives AAAI 2021 Theoretical bounds on estimation error for meta-learning ICLR 2021 Theoretically Principled Deep RL Acceleration via Nearest Neighbor Function Approximation AAAI 2021 The Parameterized Complexity of Clustering Incomplete Data AAAI 2021 The Pareto Frontier of model selection for general Contextual Bandits NeurIPS 2021 The Power of Adaptivity for Stochastic Submodular Cover ICML 2021 The Power of Factorial Powers: New Parameter settings for (Stochastic) Optimization ACML 2021 The Power of Log-Sum-Exp: Sequential Density Ratio Matrix Estimation for Speed-Accuracy Optimization ICML 2021 The promises and pitfalls of deep kernel learning UAI 2021 The Recurrent Neural Tangent Kernel ICLR 2021 The Ridgelet Prior: A Covariance Function Approach to Prior Specification for Bayesian Neural Networks JMLR 2021 The Risks of Invariant Risk Minimization ICLR 2021 The Role of Momentum Parameters in the Optimal Convergence of Adaptive Polyak's Heavy-ball Methods ICLR 2021 The Sample Complexity of Level Set Approximation AISTATS 2021 The Sample Complexity of Robust Covariance Testing COLT 2021