Randomized linear programming solves the Markov decision problem in nearly linear (sometimes sublinear) time

von Wang, Mengdi
Veröffentlicht in Mathematics of operations research (2020)

Stabilization of stochastic iterative methods for singular and nearly singular linear systems

von Wang, Mengdi
Veröffentlicht in Mathematics of operations research (2014)

Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks

von Yang, Shuoguang
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 1 of 50 (2023)

STATE AGGREGATION LEARNING FROM MARKOV TRANSITION DATA

von Duan, Yagi
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 6 of 20 (2020)

HIGH-DIMENSIONAL SPARSE LINEAR BANDITS

von Hao, Botao
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 13 of 27 (2021)

Research on Human-Machine Interface Interaction Preferences Under the Situation of New Energy Vehicles Based on Driving Scenarios

von Ding, Wei
Veröffentlicht in International Conference on Human-Computer Interaction (25. : 2023 : Kopenhagen; Online) HCI International 2023 posters ; Part 5 (2023)

Communication Efficient Distributed Learning for Kernelized Contextual Bandits

von Li, Chuanhao
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 26 of 50 (2023)

Off-Policy Fitted Q-Evaluation with Differentiable Function Approximators: Z-Estimation and Inference Theory

von Zhang, Ruiqi
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 32 of 33 (2023)

LEARNING LOW-DIMENSIONAL STATE EMBEDDINGS AND METASTABLE CLUSTERS FROM TIME SERIES DATA

von Sun, Yifan
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 6 of 20 (2020)

Optimal Estimation of Policy Gradient Via Double Fitted Iteration

von Ni, Chengzhuo
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 20 of 33 (2023)

SPARSE FEATURE SELECTION MAKES BATCH REINFORCEMENT LEARNING MORE SAMPLE EFFICIENT

von HAO, BOTAO
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 6 of 16 (2022)

Spatial pattern and micro-location rules of tourism businesses in historic towns : a case study of Pingyao, China

von Wang, Mengdi
Veröffentlicht in Journal of destination marketing & management (2022)

PROVABLY EFFICIENT REINFORCEMENT LEARNING WITH KERNEL AND NEURAL FUNCTION APPROXIMATIONS

von Yang, Zhuoran
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 17 of 27 (2021)

On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method

von Zhang, Junyu
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 3 of 36 (2022)

The Construction of Intelligent Grasping System Based on EEG

von Wang, Mengdi
Veröffentlicht in ICIRA (16. : 2023 : Hangzhou) Intelligent robotics and applications ; Part 5 (2023)

Variational Policy Gradient Method for Reinforcement Learning with General Utilities

von Zhang, Junyu
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 6 of 27 (2021)

GENERALIZED LEVERAGE SCORE SAMPLING FOR NEURAL NETWORKS

von Lee, Jason D.
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 13 of 27 (2021)

BOOTSTRAPPING FITTED Q-EVALUATION FOR OFF-POLICY INFERENCE

von HAO, BOTAO
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 6 of 16 (2022)

Efficient Reinforcement Learning in Block MDPs: A Model-Free Representation Learning Approach

von Zhang, Xuezhou
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 32 of 33 (2023)

Bandit Theory and Thompson Sampling-Guided Directed Evolution for Sequence Optimization

von Yuan, Hui
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 49 of 50 (2023)