1 code implementation • 1 Apr 2024 • Fengtao Zhou, Yingxue Xu, Yanfen Cui, Shenyan Zhang, Yun Zhu, Weiyang He, Jiguang Wang, Xin Wang, Ronald Chan, Louis Ho Shing Lau, Chu Han, Dafu Zhang, Zhenhui Li, Hao Chen
The limited availability of modalities for each patient would cause information loss, adversely affecting predictive accuracy.
1 code implementation • 3 Oct 2022 • Chumeng Liang, Zherui Huang, Yicheng Liu, Zhanyu Liu, Guanjie Zheng, Hanyuan Shi, Kan Wu, Yuhao Du, Fuliang Li, Zhenhui Li
To the best of our knowledge, CBLab is the first infrastructure supporting traffic control policy optimization in large-scale urban scenarios.
no code implementations • 19 Jun 2021 • Hua Wei, Deheng Ye, Zhao Liu, Hao Wu, Bo Yuan, Qiang Fu, Wei Yang, Zhenhui Li
While most research focuses on the state-action function part through reducing the bootstrapping error in value function approximation induced by the distribution shift of training data, the effects of error propagation in generative modeling have been neglected.
no code implementations • 20 May 2021 • Guanjie Zheng, Hanyang Liu, Kai Xu, Zhenhui Li
Traffic simulators act as an essential component in the operating and planning of transportation systems.
no code implementations • 18 May 2021 • Chang Liu, Guanjie Zheng, Zhenhui Li
Therefore, in this paper, we propose to learn the human routing model, which is one of the most essential part in the traffic simulator.
no code implementations • 22 Mar 2021 • Hua Wei, Chacha Chen, Chang Liu, Guanjie Zheng, Zhenhui Li
Simulation of the real-world traffic can be used to help validate the transportation policies.
no code implementations • 31 Dec 2020 • Hongjian Wang, Qi Li, Lanbo Zhang, Yue Lu, Steven Yoo, Srinivas Vadrevu, Zhenhui Li
Historical features are important in ads click-through rate (CTR) prediction, because they account for past engagements between users and ads.
no code implementations • NeurIPS 2020 • Huaxiu Yao, Yingbo Zhou, Mehrdad Mahdavi, Zhenhui Li, Richard Socher, Caiming Xiong
When a new task is encountered, it constructs a meta-knowledge pathway by either utilizing the most relevant knowledge blocks or exploring new blocks.
1 code implementation • 26 Jul 2020 • Huaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying WEI, Li Tian, James Zou, Junzhou Huang, Zhenhui Li
Moreover, both MetaMix and Channel Shuffle outperform state-of-the-art results by a large margin across many datasets and are compatible with existing meta-learning algorithms.
no code implementations • 1 Mar 2020 • Hua Wei, Dongkuan Xu, Junjie Liang, Zhenhui Li
To the best of our knowledge, we are the first to learn to model the state transition of moving agents with system dynamics.
no code implementations • 9 Jan 2020 • Porter Jenkins, Hua Wei, J. Stockton Jenkins, Zhenhui Li
Moreover, learning important spatial patterns in offline retail is challenging due to the scarcity of data and the high cost of exploration and experimentation in the physical world.
1 code implementation • ICLR 2020 • Huaxiu Yao, Xian Wu, Zhiqiang Tao, Yaliang Li, Bolin Ding, Ruirui Li, Zhenhui Li
In order to efficiently learn with small amount of data on new tasks, meta-learning transfers knowledge learned from previous tasks to the new ones.
1 code implementation • 26 Nov 2019 • Chuxu Zhang, Huaxiu Yao, Chao Huang, Meng Jiang, Zhenhui Li, Nitesh V. Chawla
Knowledge graphs (KGs) serve as useful resources for various natural language processing applications.
1 code implementation • 7 Oct 2019 • Huaxiu Yao, Chuxu Zhang, Ying WEI, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh V. Chawla, Zhenhui Li
Towards the challenging problem of semi-supervised node classification, there have been extensive studies.
no code implementations • 29 Aug 2019 • Guanjie Zheng, Mengqi Liu, Tao Wen, Hongjian Wang, Huaxiu Yao, Susan L. Brantley, Zhenhui Li
In the face of growing needs for water and energy, a fundamental understanding of the environmental impacts of human activities becomes critical for managing water and energy resources, remedying water pollution, and making regulatory policy wisely.
1 code implementation • 13 May 2019 • Huichu Zhang, Siyuan Feng, Chang Liu, Yaoyao Ding, Yichen Zhu, Zihan Zhou, Wei-Nan Zhang, Yong Yu, Haiming Jin, Zhenhui Li
The most commonly used open-source traffic simulator SUMO is, however, not scalable to large road network and large traffic flow, which hinders the study of reinforcement learning on traffic scenarios.
Multi-agent Reinforcement Learning reinforcement-learning +1
1 code implementation • 13 May 2019 • Huaxiu Yao, Ying WEI, Junzhou Huang, Zhenhui Li
In order to learn quickly with few samples, meta-learning utilizes prior knowledge learned from previous tasks.
no code implementations • 12 May 2019 • Guanjie Zheng, Xinshi Zang, Nan Xu, Hua Wei, Zhengyao Yu, Vikash Gayah, Kai Xu, Zhenhui Li
In this paper, we propose to re-examine the RL approaches through the lens of classic transportation theory.
1 code implementation • 12 May 2019 • Guanjie Zheng, Yuanhao Xiong, Xinshi Zang, Jie Feng, Hua Wei, Huichu Zhang, Yong Li, Kai Xu, Zhenhui Li
Increasingly available city data and advanced learning techniques have empowered people to improve the efficiency of our city functions.
4 code implementations • 11 May 2019 • Hua Wei, Nan Xu, Huichu Zhang, Guanjie Zheng, Xinshi Zang, Chacha Chen, Wei-Nan Zhang, Yanmin Zhu, Kai Xu, Zhenhui Li
To enable cooperation of traffic signals, in this paper, we propose a model, CoLight, which uses graph attentional networks to facilitate communication.
no code implementations • 17 Apr 2019 • Hua Wei, Guanjie Zheng, Vikash Gayah, Zhenhui Li
Traffic signal control is an important and challenging real-world problem, which aims to minimize the travel time of vehicles by coordinating their movements at the road intersections.
1 code implementation • 24 Jan 2019 • Huaxiu Yao, Yiding Liu, Ying WEI, Xianfeng Tang, Zhenhui Li
Specifically, our proposed model is designed as a spatial-temporal network with a meta-learning paradigm.
no code implementations • 26 Aug 2018 • Yu-Hsuan Kuo, Zhenhui Li, Daniel Kifer
Advances in sensor technology have enabled the collection of large-scale datasets.
5 code implementations • 3 Mar 2018 • Huaxiu Yao, Xianfeng Tang, Hua Wei, Guanjie Zheng, Zhenhui Li
Although both factors have been considered in modeling, existing works make strong assumptions about spatial dependence and temporal dynamics, i. e., spatial dependence is stationary in time, and temporal dynamics is strictly periodical.
1 code implementation • 23 Feb 2018 • Huaxiu Yao, Fei Wu, Jintao Ke, Xianfeng Tang, Yitian Jia, Siyu Lu, Pinghua Gong, Jieping Ye, Zhenhui Li
Traditional demand prediction methods mostly rely on time series forecasting techniques, which fail to model the complex non-linear spatial and temporal relations.
no code implementations • 28 Dec 2015 • Hongjian Wang, Zhenhui Li, Yu-Hsuan Kuo, Dan Kifer
The increased availability of large-scale trajectory data around the world provides rich information for the study of urban dynamics.
1 code implementation • 14 Feb 2012 • Quanquan Gu, Zhenhui Li, Jiawei Han
Fisher score is one of the most widely used supervised feature selection methods.