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Optimization

14,850 papers (55 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Continuous Optimization (4,424) Stochastic Methods (2,991) Combinatorial Optimization (2,615) Online Algorithms (2,404) Optimization (1,521) Game Theory (1,046) Convex Optimization (864) Discrete Optimization (721) Optimal Transport (474) Sparse Optimization (416) Optimal Control (271) Global Optimization (200) Non-Convex Optimization (182) Distributed Learning (164) Approximation Algorithms (162) Multi-Objective Optimization (151) Distributed Optimization (136) Bayesian Optimization (132) Theory (109) Compressed Sensing (102) Algorithms (89) Robust Optimization (86) Submodular Optimization (77) Kernel Methods (75) Evolutionary Algorithm (72) Linear Programming (54) Tensor Decomposition (48) Bilevel Optimization (42) Integer Programming (38) Matrix Completion (33) Algorithm (21) Regularization (11)

Papers per year

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16
133
440
1,353
1,441
2000
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Papers (including subtopics)

A PTAS for the Bayesian Thresholding Bandit Problem AISTATS 2020 A Randomized Algorithm to Reduce the Support of Discrete Measures NeurIPS 2020 A Reinforcement Learning Approach to Strategic Belief Revelation with Social Influence AAAI 2020 A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees NeurIPS 2020 A shooting formulation of deep learning NeurIPS 2020 A Simple and Efficient Smoothing Method for Faster Optimization and Local Exploration NeurIPS 2020 A Simple Approach for Non-stationary Linear Bandits AISTATS 2020 A Simple, Fast, and Safe Mediator for Congestion Management AAAI 2020 A single algorithm for both restless and rested rotting bandits AISTATS 2020 A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems NeurIPS 2020 A Single Recipe for Online Submodular Maximization with Adversarial or Stochastic Constraints NeurIPS 2020 A Sparse Resultant Based Method for Efficient Minimal Solvers CVPR 2020 A Sparse Semismooth Newton Based Proximal Majorization-Minimization Algorithm for Nonconvex Square-Root-Loss Regression Problems JMLR 2020 A Spectral Method for Unsupervised Multi-Document Summarization EMNLP 2020 A State Aggregation Approach for Solving Knapsack Problem with Deep Reinforcement Learning ACML 2020 A Stochastic Derivative-Free Optimization Method with Importance Sampling: Theory and Learning to Control AAAI 2020 A Stochastic Derivative Free Optimization Method with Momentum ICLR 2020 A Swiss Army Knife for Minimax Optimal Transport ICML 2020 Asymptotically Optimal Exact Minibatch Metropolis-Hastings NeurIPS 2020 Asymptotic Analysis of Sampling Estimators for Randomized Numerical Linear Algebra Algorithms AISTATS 2020 Asymptotic Analysis via Stochastic Differential Equations of Gradient Descent Algorithms in Statistical and Computational Paradigms JMLR 2020 Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance NeurIPS 2020 Asymptotic Risk of Bézier Simplex Fitting AAAI 2020 A Three-Level Optimization Model for Nonlinearly Separable Clustering AAAI 2020 A Tight Convergence Analysis for Stochastic Gradient Descent with Delayed Updates ALT 2020