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Jieping Ye

Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions

Jul 25, 2022
Shuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang

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* ICML 2021

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Stochastic Gradient Descent without Full Data Shuffle

Jun 12, 2022
Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cedric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang

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* This technical report is an extension of our SIGMOD 2022 paper titled "In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle". https://doi.org/10.1145/3514221.3526150

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Rethinking Graph Convolutional Networks in Knowledge Graph Completion

Feb 08, 2022
Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu

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* Accepted to WWW 2022

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On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game

Oct 19, 2021
Shuang Qiu, Jieping Ye, Zhaoran Wang, Zhuoran Yang

* ICML 2021

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A Deep Value-network Based Approach for Multi-Driver Order Dispatching

Jun 08, 2021
Xiaocheng Tang, Zhiwei Qin, Fan Zhang, Zhaodong Wang, Zhe Xu, Yintai Ma, Hongtu Zhu, Jieping Ye

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* KDD 2019 Oral

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Value Function is All You Need: A Unified Learning Framework for Ride Hailing Platforms

Jun 04, 2021
Xiaocheng Tang, Fan Zhang, Zhiwei Qin, Yansheng Wang, Dingyuan Shi, Bingchen Song, Yongxin Tong, Hongtu Zhu, Jieping Ye

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* KDD 2021; Ride-hailing marketplace open simulation platform: https://outreach.didichuxing.com/Simulation/

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Reinforcement Learning for Ridesharing: A Survey

May 03, 2021
Zhiwei Qin, Hongtu Zhu, Jieping Ye

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