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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)

Active Local Learning COLT 2020 Active Model Estimation in Markov Decision Processes UAI 2020 Active Preference-Based Gaussian Process Regression for Reward Learning RSS 2020 Active Testing: An Unbiased Evaluation Method for Distantly Supervised Relation Extraction EMNLP 2020 AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients NeurIPS 2020 AdaGrad stepsizes: Sharp convergence over nonconvex landscapes JMLR 2020 Adam with Bandit Sampling for Deep Learning NeurIPS 2020 Adaptation Properties Allow Identification of Optimized Neural Codes NeurIPS 2020 Adapting Stable Matchings to Evolving Preferences AAAI 2020 Adapting Text Embeddings for Causal Inference UAI 2020 Adapting to Misspecification in Contextual Bandits NeurIPS 2020 Adapting to Smoothness: A More Universal Algorithm for Online Convex Optimization AAAI 2020 Adaptive Approximation and Generalization of Deep Neural Network with Intrinsic Dimensionality JMLR 2020 Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE ICML 2020 Adaptive Convolutional ReLUs AAAI 2020 Adaptive Correlated Monte Carlo for Contextual Categorical Sequence Generation ICLR 2020 Adaptive Discretization for Model-Based Reinforcement Learning NeurIPS 2020 Adaptive, Distribution-Free Prediction Intervals for Deep Networks AISTATS 2020 Adaptive Double-Exploration Tradeoff for Outlier Detection AAAI 2020 Adaptive Estimator Selection for Off-Policy Evaluation ICML 2020 Adaptive Experimental Design with Temporal Interference: A Maximum Likelihood Approach NeurIPS 2020 Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions AAAI 2020 Adaptive Gradient Descent without Descent ICML 2020 Adaptive Gradient Quantization for Data-Parallel SGD NeurIPS 2020 Adaptive Greedy versus Non-Adaptive Greedy for Influence Maximization AAAI 2020