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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)

Projection & Probability-Driven Black-Box Attack CVPR 2020 Projective Preferential Bayesian Optimization ICML 2020 Proper Learning, Helly Number, and an Optimal SVM Bound COLT 2020 Prophet Inequalities for Bayesian Persuasion IJCAI 2020 Prophets, Secretaries, and Maximizing the Probability of Choosing the Best AISTATS 2020 Proportionality in Approval-Based Elections With a Variable Number of Winners IJCAI 2020 Protean: VM Allocation Service at Scale OSDI 2020 Protecting Geolocation Privacy of Photo Collections AAAI 2020 Provable Benefit of Orthogonal Initialization in Optimizing Deep Linear Networks ICLR 2020 Provable Convex Co-clustering of Tensors JMLR 2020 Provable guarantees for decision tree induction: the agnostic setting ICML 2020 Provable Online CP/PARAFAC Decomposition of a Structured Tensor via Dictionary Learning NeurIPS 2020 Provable robustness against all adversarial l_p-perturbations for p≥ 1 ICLR 2020 Provable Smoothness Guarantees for Black-Box Variational Inference ICML 2020 Provably adaptive reinforcement learning in metric spaces NeurIPS 2020 Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation ICML 2020 Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning NeurIPS 2020 Provably Efficient Exploration in Policy Optimization ICML 2020 Provably Efficient Model-based Policy Adaptation ICML 2020 Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial Approach NeurIPS 2020 Provably Efficient Neural GTD for Off-Policy Learning NeurIPS 2020 Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits NeurIPS 2020 Provably Efficient Reinforcement Learning with Kernel and Neural Function Approximations NeurIPS 2020 Provably efficient reinforcement learning with linear function approximation COLT 2020 Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration NeurIPS 2020