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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

1
52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Safe-Bayesian Generalized Linear Regression AISTATS 2020 Safe Linear Stochastic Bandits AAAI 2020 Safe Motion Planning for Autonomous Driving using an Adversarial Road Model RSS 2020 Safe non-smooth black-box optimization with application to policy search L4DC 2020 Sample Amplification: Increasing Dataset Size even when Learning is Impossible ICML 2020 Sample complexity and effective dimension for regression on manifolds NeurIPS 2020 Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors ICML 2020 Sample complexity bounds for localized sketching AISTATS 2020 Sample Complexity Bounds for RNNs with Application to Combinatorial Graph Problems (Student Abstract) AAAI 2020 Sample Complexity of Estimating the Policy Gradient for Nearly Deterministic Dynamical Systems AISTATS 2020 Sample Complexity of Kalman Filtering for Unknown Systems L4DC 2020 Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles AISTATS 2020 Sample Complexity of Uniform Convergence for Multicalibration NeurIPS 2020 Sample-efficient Cross-Entropy Method for Real-time Planning CoRL 2020 Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining NeurIPS 2020 Sample Efficient Policy Gradient Methods with Recursive Variance Reduction ICLR 2020 Sample-Efficient Reinforcement Learning of Undercomplete POMDPs NeurIPS 2020 Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation NeurIPS 2020 Sampling-based Reachability Analysis: A Random Set Theory Approach with Adversarial Sampling CoRL 2020 Sampling from a k-DPP without looking at all items NeurIPS 2020 Sampling Without Compromising Accuracy in Adaptive Data Analysis ALT 2020 Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot NeurIPS 2020 SCAFFOLD: Stochastic Controlled Averaging for Federated Learning ICML 2020 Scalable and Flexible Clustering of Grouped Data via Parallel and Distributed Sampling in Versatile Hierarchical Dirichlet Processes UAI 2020 Scalable and Generalizable Social Bot Detection through Data Selection AAAI 2020