Search Results for author: Zhenhui Li

Found 25 papers, 12 papers with code

Boosting Offline Reinforcement Learning with Residual Generative Modeling

no code implementations19 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.

Offline RL Q-Learning +1

Objective-aware Traffic Simulation via Inverse Reinforcement Learning

no code implementations20 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.

reinforcement-learning

Learning to Route via Theory-Guided Residual Network

no code implementations18 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.

Learning to Simulate on Sparse Trajectory Data

no code implementations22 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.

Imitation Learning

Automatic Historical Feature Generation through Tree-based Method in Ads Prediction

no code implementations31 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.

Click-Through Rate Prediction online learning

Online Structured Meta-learning

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.

Meta-Learning

Improving Generalization in Meta-learning via Task Augmentation

1 code implementation26 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.

Meta-Learning

How Do We Move: Modeling Human Movement with System Dynamics

no code implementations1 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.

Imitation Learning

A Probabilistic Simulator of Spatial Demand for Product Allocation

no code implementations9 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.

Q-Learning

Automated Relational Meta-learning

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.

Few-Shot Image Classification Meta-Learning

Few-Shot Knowledge Graph Completion

1 code implementation26 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.

Knowledge Graph Completion Natural Language Processing +1

Targeted Source Detection for Environmental Data

no code implementations29 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.

CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario

1 code implementation13 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

Learning Phase Competition for Traffic Signal Control

1 code implementation12 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.

Diagnosing Reinforcement Learning for Traffic Signal Control

no code implementations12 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.

reinforcement-learning

CoLight: Learning Network-level Cooperation for Traffic Signal Control

3 code implementations11 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.

Multi-agent Reinforcement Learning

A Survey on Traffic Signal Control Methods

no code implementations17 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.

reinforcement-learning

Detecting Outliers in Data with Correlated Measures

no code implementations26 Aug 2018 Yu-Hsuan Kuo, Zhenhui Li, Daniel Kifer

Advances in sensor technology have enabled the collection of large-scale datasets.

Outlier Detection

Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction

4 code implementations3 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.

Traffic Prediction

Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction

1 code implementation23 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.

Image Classification Time Series +2

A Simple Baseline for Travel Time Estimation using Large-Scale Trip Data

no code implementations28 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.

Generalized Fisher Score for Feature Selection

1 code implementation14 Feb 2012 Quanquan Gu, Zhenhui Li, Jiawei Han

Fisher score is one of the most widely used supervised feature selection methods.

feature selection

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