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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)

Solving PDE-Constrained Control Problems Using Operator Learning AAAI 2022 Solving Stackelberg Prediction Game with Least Squares Loss via Spherically Constrained Least Squares Reformulation ICML 2022 Span-Based Semantic Role Labeling with Argument Pruning and Second-Order Inference AAAI 2022 Sparse Mixed Linear Regression with Guarantees: Taming an Intractable Problem with Invex Relaxation ICML 2022 Sparsification of Decomposable Submodular Functions AAAI 2022 Sparsity in Partially Controllable Linear Systems ICML 2022 Spectral risk-based learning using unbounded losses AISTATS 2022 Spectral Robustness for Correlation Clustering Reconstruction in Semi-Adversarial Models AISTATS 2022 Speeding up approximate MAP by applying domain knowledge about relevant variables PGM 2022 Speeding Up the RUL¯ Dynamic-Controllability-Checking Algorithm for Simple Temporal Networks with Uncertainty AAAI 2022 Spline-PINN: Approaching PDEs without Data Using Fast, Physics-Informed Hermite-Spline CNNs AAAI 2022 Stability and Generalization for Markov Chain Stochastic Gradient Methods NeurIPS 2022 State Dependent Performative Prediction with Stochastic Approximation AISTATS 2022 Statistical and Computational Phase Transitions in Group Testing COLT 2022 Statistical inference with implicit SGD: proximal Robbins-Monro vs. Polyak-Ruppert ICML 2022 Statistical Learning and Inverse Problems: A Stochastic Gradient Approach NeurIPS 2022 Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers NeurIPS 2022 Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances NeurIPS 2022 Steering vector correction in MVDR beamformer for speech enhancement Interspeech 2022 Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models ICML 2022 Stochastic Continuous Submodular Maximization: Boosting via Non-oblivious Function ICML 2022 Stochastic DCA with Variance Reduction and Applications in Machine Learning JMLR 2022 Stochastic Extragradient: General Analysis and Improved Rates AISTATS 2022 Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusions NeurIPS 2022 Stochastic linear optimization never overfits with quadratically-bounded losses on general data COLT 2022