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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)

Filter Response Normalization Layer: Eliminating Batch Dependence in the Training of Deep Neural Networks CVPR 2020 Finding All ε-Good Arms in Stochastic Bandits NeurIPS 2020 Finding Good Subtrees for Constraint Optimization Problems Using Frequent Pattern Mining AAAI 2020 Finding Intelligible Consonant-Vowel Sounds Using High-Quality Articulatory Synthesis Interspeech 2020 Finding Most Compatible Phylogenetic Trees over Multi-State Characters AAAI 2020 Finding Second-Order Stationary Points Efficiently in Smooth Nonconvex Linearly Constrained Optimization Problems NeurIPS 2020 Finding trainable sparse networks through Neural Tangent Transfer ICML 2020 Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent ICML 2020 Fine-Grained Machine Teaching with Attention Modeling AAAI 2020 Fine-Grained Replicated State Machines for a Cluster Storage System NSDI 2020 Fine-Grained View on Bribery for Group Identification IJCAI 2020 Finer Metagenomic Reconstruction via Biodiversity Optimization NeurIPS 2020 Finite Depth and Width Corrections to the Neural Tangent Kernel ICLR 2020 Finite-Memory Near-Optimal Learning for Markov Decision Processes with Long-Run Average Reward UAI 2020 Finite Regret and Cycles with Fixed Step-Size via Alternating Gradient Descent-Ascent COLT 2020 Finite-Sample Analysis of Contractive Stochastic Approximation Using Smooth Convex Envelopes NeurIPS 2020 Finite-sample Analysis of Greedy-GQ with Linear Function Approximation under Markovian Noise UAI 2020 Finite Sample System Identification: Optimal Rates and the Role of Regularization L4DC 2020 Finite-Time Analysis for Double Q-learning NeurIPS 2020 Finite-Time Analysis of Asynchronous Stochastic Approximation and Q-Learning COLT 2020 Finite-Time Analysis of Decentralized Temporal-Difference Learning with Linear Function Approximation AISTATS 2020 Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise COLT 2020 Finite-Time Analysis of Round-Robin Kullback-Leibler Upper Confidence Bounds for Optimal Adaptive Allocation with Multiple Plays and Markovian Rewards NeurIPS 2020 Finite-Time Convergence in Continuous-Time Optimization ICML 2020 Finite-Time Error Bounds for Biased Stochastic Approximation with Applications to Q-Learning AISTATS 2020