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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
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828
3,646
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2000
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Papers (including subtopics)

Momentum Improves Normalized SGD ICML 2020 Momentum in Reinforcement Learning AISTATS 2020 MomentumRNN: Integrating Momentum into Recurrent Neural Networks NeurIPS 2020 Moniqua: Modulo Quantized Communication in Decentralized SGD ICML 2020 Monotone operator equilibrium networks NeurIPS 2020 Monte Carlo Gradient Estimation in Machine Learning JMLR 2020 Monte-Carlo Graph Search: the Value of Merging Similar States ACML 2020 Monte-Carlo Tree Search as Regularized Policy Optimization ICML 2020 Monte-Carlo Tree Search in Continuous Action Spaces with Value Gradients AAAI 2020 Monte Carlo Tree Search in Continuous Spaces Using Voronoi Optimistic Optimization with Regret Bounds AAAI 2020 More Accurate Learning of k-DNF Reference Classes AAAI 2020 More Data Can Expand The Generalization Gap Between Adversarially Robust and Standard Models ICML 2020 MOReL: Model-Based Offline Reinforcement Learning NeurIPS 2020 More Powerful Selective Kernel Tests for Feature Selection AISTATS 2020 Most ReLU Networks Suffer from ℓ^2 Adversarial Perturbations NeurIPS 2020 Moving in the Right Direction: A Regularization for Deep Metric Learning CVPR 2020 MRFMap: Online Probabilistic 3D Mapping using Forward Ray Sensor Models RSS 2020 MSG-GAN: Multi-Scale Gradients for Generative Adversarial Networks CVPR 2020 MTL-NAS: Task-Agnostic Neural Architecture Search Towards General-Purpose Multi-Task Learning CVPR 2020 Multiagent Rollout and Policy Iteration for POMDP with Application to Multi-Robot Repair Problems CoRL 2020 Multi-attribute Bayesian optimization with interactive preference learning AISTATS 2020 Multichannel Color Image Denoising via Weighted Schatten p-norm Minimization IJCAI 2020 Multiclass Neural Network Minimization via Tropical Newton Polytope Approximation ICML 2020 Multidimensional Shape Constraints ICML 2020 Multifaceted Uncertainty Estimation for Label-Efficient Deep Learning NeurIPS 2020