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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)

Learning Continuous Graph Structure with Bilevel Programming for Graph Neural Networks IJCAI 2022 Learning Distributed Channel Access Policies for Networked Estimation: Data-driven Optimization in the Mean-field Regime L4DC 2022 Learning Efficient and Robust Ordinary Differential Equations via Invertible Neural Networks ICML 2022 Learning-Enabled Robust Control with Noisy Measurements L4DC 2022 Learning from a Learning User for Optimal Recommendations ICML 2022 Learning from a Sample in Online Algorithms NeurIPS 2022 Learning from Distributed Users in Contextual Linear Bandits Without Sharing the Context NeurIPS 2022 Learning in Congestion Games with Bandit Feedback NeurIPS 2022 Learning in Stochastic Monotone Games with Decision-Dependent Data AISTATS 2022 Learning interacting dynamical systems with latent Gaussian process ODEs NeurIPS 2022 Learning large Bayesian networks with expert constraints UAI 2022 Learning Large DAGs by Combining Continuous Optimization and Feedback Arc Set Heuristics AAAI 2022 Learning Linear Models Using Distributed Iterative Hessian Sketching L4DC 2022 Learning Low Degree Hypergraphs COLT 2022 Learning Markov Games with Adversarial Opponents: Efficient Algorithms and Fundamental Limits ICML 2022 Learning Mixed Multinomial Logits with Provable Guarantees NeurIPS 2022 Learning NP-Hard Multi-Agent Assignment Planning using GNN: Inference on a Random Graph and Provable Auction-Fitted Q-learning NeurIPS 2022 Learning on the Edge: Online Learning with Stochastic Feedback Graphs NeurIPS 2022 Learning Predictions for Algorithms with Predictions NeurIPS 2022 Learning Synthetic Environments and Reward Networks for Reinforcement Learning ICLR 2022 Learning the Optimal Recommendation from Explorative Users AAAI 2022 Learning the Structure of Large Networked Systems Obeying Conservation Laws NeurIPS 2022 Learning to Branch with Tree MDPs NeurIPS 2022 Learning to Compare Nodes in Branch and Bound with Graph Neural Networks NeurIPS 2022 Learning to Control Linear Systems can be Hard COLT 2022