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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)

The Product Cut NeurIPS 2016 The SNOW Theorem and Latency-Optimal Read-Only Transactions OSDI 2016 The Sound of APALM Clapping: Faster Nonsmooth Nonconvex Optimization with Stochastic Asynchronous PALM NeurIPS 2016 Threshold Bandits, With and Without Censored Feedback NeurIPS 2016 Tight Complexity Bounds for Optimizing Composite Objectives NeurIPS 2016 Tight (Lower) Bounds for the Fixed Budget Best Arm Identification Bandit Problem COLT 2016 Tightness of LP Relaxations for Almost Balanced Models AISTATS 2016 Time and Energy Optimal Path Planning in General Flows RSS 2016 Time-Varying Gaussian Process Bandit Optimization AISTATS 2016 Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear Smoothers NeurIPS 2016 Towards Faster Rates and Oracle Property for Low-Rank Matrix Estimation ICML 2016 Towards More Efficient SPSD Matrix Approximation and CUR Matrix Decomposition JMLR 2016 Towards Unifying Hamiltonian Monte Carlo and Slice Sampling NeurIPS 2016 Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient ICML 2016 Tracking the Best Expert in Non-stationary Stochastic Environments NeurIPS 2016 Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization AISTATS 2016 Training Neural Networks Without Gradients: A Scalable ADMM Approach ICML 2016 Trend Filtering on Graphs JMLR 2016 Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation NeurIPS 2016 Trust No One: Low Rank Matrix Factorization Using Hierarchical RANSAC CVPR 2016 Uncalibrated Photometric Stereo by Stepwise Optimization Using Principal Components of Isotropic BRDFs CVPR 2016 Unified Methods for Exploiting Piecewise Linear Structure in Convex Optimization NeurIPS 2016 Unwrapping ADMM: Efficient Distributed Computing via Transpose Reduction AISTATS 2016 Using Relevant Public Posts to Enhance News Article Summarization COLING 2016 Variational Inference in Mixed Probabilistic Submodular Models NeurIPS 2016