b'Jieping Ye'

research

∙ 02/22/2022

Policy Evaluation for Temporal and/or Spatial Dependent Experiments in Ride-sourcing Platforms

Policy evaluation based on A/B testing has attracted considerable intere...

Shikai Luo, et al. ∙

research

∙ 10/19/2021

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

To achieve sample efficiency in reinforcement learning (RL), it necessit...

Shuang Qiu, et al. ∙

research

∙ 06/08/2021

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

Recent works on ride-sharing order dispatching have highlighted the impo...

Xiaocheng Tang, et al. ∙

research

∙ 05/18/2021

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

Large ride-hailing platforms, such as DiDi, Uber and Lyft, connect tens ...

Xiaocheng Tang, et al. ∙

research

∙ 05/03/2021

Reinforcement Learning for Ridesharing: A Survey

In this paper, we present a comprehensive, in-depth survey of the litera...

Zhiwei Qin, et al. ∙

research

∙ 03/08/2021

Real-world Ride-hailing Vehicle Repositioning using Deep Reinforcement Learning

We present a new practical framework based on deep reinforcement learnin...

Yan Jiao, et al. ∙

research

∙ 12/14/2020

Successive Projection for Solving Systems of Nonlinear Equations/Inequalities

Solving large-scale systems of nonlinear equations/inequalities is a fun...

Wen-Jun Zeng, et al. ∙

research

∙ 12/07/2020

Selective Pseudo-Labeling with Reinforcement Learning for Semi-Supervised Domain Adaptation

Recent domain adaptation methods have demonstrated impressive improvemen...

Bingyu Liu, et al. ∙

research

∙ 12/03/2020

Domain Adaptation with Incomplete Target Domains

Domain adaptation, as a task of reducing the annotation cost in a target...

Zhenpeng Li, et al. ∙

research

∙ 11/14/2020

Bi-Dimensional Feature Alignment for Cross-Domain Object Detection

Recently the problem of cross-domain object detection has started drawin...

Zhen Zhao, et al. ∙

research

∙ 11/11/2020

Joint predictions of multi-modal ride-hailing demands: a deep multi-task multigraph learning-based approach

Ride-hailing platforms generally provide various service options to cust...

Jintao Ke, et al. ∙

research

∙ 11/05/2020

Robust Unsupervised Video Anomaly Detection by Multi-Path Frame Prediction

Video anomaly detection is commonly used in many applications such as se...

Xuanzhao Wang, et al. ∙

research

∙ 10/16/2020

DiDi's Machine Translation System for WMT2020

This paper describes DiDi AI Labs' submission to the WMT2020 news transl...

Tanfang Chen, et al. ∙

research

∙ 10/15/2020

Knowledge Transfer in Multi-Task Deep Reinforcement Learning for Continuous Control

While Deep Reinforcement Learning (DRL) has emerged as a promising appro...

Zhiyuan Xu, et al. ∙

research

∙ 10/09/2020

Meta Graph Attention on Heterogeneous Graph with Node-Edge Co-evolution

Graph neural networks have become an important tool for modeling structu...

Yucheng Lin, et al. ∙

research

∙ 09/06/2020

Learning from Very Few Samples: A Survey

Few sample learning (FSL) is significant and challenging in the field of...

Jiang Lu, et al. ∙

research

∙ 08/23/2020

Single-Timescale Stochastic Nonconvex-Concave Optimization for Smooth Nonlinear TD Learning

Temporal-Difference (TD) learning with nonlinear smooth function approxi...

Shuang Qiu, et al. ∙

research

∙ 08/07/2020

Predicting Individual Treatment Effects of Large-scale Team Competitions in a Ride-sharing Economy

Millions of drivers worldwide have enjoyed financial benefits and work s...

Teng Ye, et al. ∙

research

∙ 06/25/2020

PropagationNet: Propagate Points to Curve to Learn Structure Information

Deep learning technique has dramatically boosted the performance of face...

Xiehe Huang, et al. ∙

research

∙ 06/24/2020

Road Network Metric Learning for Estimated Time of Arrival

Recently, deep learning have achieved promising results in Estimated Tim...

Yiwen Sun, et al. ∙

research

∙ 06/08/2020

Ensemble Model with Batch Spectral Regularization and Data Blending for Cross-Domain Few-Shot Learning with Unlabeled Data

Deep learning models are difficult to obtain good performance when data ...

Zhen Zhao, et al. ∙

research

∙ 06/07/2020

FMA-ETA: Estimating Travel Time Entirely Based on FFN With Attention

Estimated time of arrival (ETA) is one of the most important services in...

Yiwen Sun, et al. ∙

research

∙ 06/07/2020

Fusion Recurrent Neural Network

Considering deep sequence learning for practical application, two repres...

Yiwen Sun, et al. ∙

research

∙ 05/18/2020

Feature Transformation Ensemble Model with Batch Spectral Regularization for Cross-Domain Few-Shot Classification

Deep learning models often require much annotated data to obtain good pe...

Bingyu Liu, et al. ∙

research

∙ 05/16/2020

Sequential Sentence Matching Network for Multi-turn Response Selection in Retrieval-based Chatbots

Recently, open domain multi-turn chatbots have attracted much interest f...

Chao Xiong, et al. ∙

research

∙ 04/23/2020

Constructing Geographic and Long-term Temporal Graph for Traffic Forecasting

Traffic forecasting influences various intelligent transportation system...

Yiwen Sun, et al. ∙

research

∙ 04/02/2020

Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation

Contextual multi-armed bandit (MAB) achieves cutting-edge performance on...

Mengyue Yang, et al. ∙

research

∙ 03/29/2020

Mutual Learning Network for Multi-Source Domain Adaptation

Early Unsupervised Domain Adaptation (UDA) methods have mostly assumed t...

Zhenpeng Li, et al. ∙

research

∙ 03/29/2020

Adaptive Object Detection with Dual Multi-Label Prediction

In this paper, we propose a novel end-to-end unsupervised deep domain ad...

Zhen Zhao, et al. ∙

research

∙ 03/17/2020

Augmented Parallel-Pyramid Net for Attention Guided Pose-Estimation

The target of human pose estimation is to determine body part or joint l...

Luanxuan Hou, et al. ∙

research

∙ 03/02/2020

Upper Confidence Primal-Dual Optimization: Stochastically Constrained Markov Decision Processes with Adversarial Losses and Unknown Transitions

We consider online learning for episodic Markov decision processes (MDPs...

Shuang Qiu, et al. ∙

research

∙ 02/05/2020

A Reinforcement Learning Framework for Time-Dependent Causal Effects Evaluation in A/B Testing

A/B testing, or online experiment is a standard business strategy to com...

Chengchun Shi, et al. ∙

research

∙ 01/20/2020

A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications

Generative adversarial networks (GANs) are a hot research topic recently...

Jie Gui, et al. ∙

research

∙ 12/19/2019

An Attention-based Graph Neural Network for Heterogeneous Structural Learning

In this paper, we focus on graph representation learning of heterogeneou...

Huiting Hong, et al. ∙

research

∙ 11/25/2019

Deep Reinforcement Learning for Multi-Driver Vehicle Dispatching and Repositioning Problem

Order dispatching and driver repositioning (also known as fleet manageme...

John Holler, et al. ∙

research

∙ 11/11/2019

Building Effective Large-Scale Traffic State Prediction System: Traffic4cast Challenge Solution

How to build an effective large-scale traffic state prediction system is...

Yang Liu, et al. ∙

research

∙ 10/17/2019

Predicting origin-destination ride-sourcing demand with a spatio-temporal encoder-decoder residual multi-graph convolutional network

With the rapid development of mobile-internet technologies, on-demand ri...

Jintao Ke, et al. ∙

research

∙ 10/07/2019

Multi-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matching

Improving the efficiency of dispatching orders to vehicles is a research...

Ming Zhou, et al. ∙

research

∙ 09/26/2019

Multi-grained Attention Networks for Single Image Super-Resolution

Deep Convolutional Neural Networks (CNN) have drawn great attention in i...

Huapeng Wu, et al. ∙

research

∙ 09/25/2019

PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions

Graph node embedding aims at learning a vector representation for all no...

Shupeng Gui, et al. ∙

research

∙ 07/12/2019

Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation

Reinforcement learning aims at searching the best policy model for decis...

Wenjie Shang, et al. ∙

research

∙ 07/11/2019

Reward Advancement: Transforming Policy under Maximum Causal Entropy Principle

Many real-world human behaviors can be characterized as a sequential dec...

Guojun Wu, et al. ∙

research

∙ 07/06/2019

AutoSlim: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates

Structured weight pruning is a representative model compression techniqu...

Ning Liu, et al. ∙

research

∙ 07/06/2019

AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates

Structured weight pruning is a representative model compression techniqu...

Ning Liu, et al. ∙

research

∙ 05/27/2019

CoRide: Joint Order Dispatching and Fleet Management for Multi-Scale Ride-Hailing Platforms

How to optimally dispatch orders to vehicles and how to trade off betwee...

Jiarui Jin, et al. ∙

research

∙ 05/27/2019

Multi-Modal Graph Interaction for Multi-Graph Convolution Network in Urban Spatiotemporal Forecasting

Graph convolution network based approaches have been recently used to mo...

Xu Geng, et al. ∙

research

∙ 05/23/2019

Where to Find Next Passengers on E-hailing Platforms? - A Markov Decision Process Approach

Vacant taxi drivers' passenger seeking process in a road network generat...

Zhenyu Shou, et al. ∙

research

∙ 05/13/2019

Object Detection in 20 Years: A Survey

Object detection, as of one the most fundamental and challenging problem...

Zhengxia Zou, et al. ∙

research

∙ 04/03/2019

D^2-City: A Large-Scale Dashcam Video Dataset of Diverse Traffic Scenarios

Driving datasets accelerate the development of intelligent driving and r...

Zhengping Che, et al. ∙

research

∙ 03/18/2019

POI Semantic Model with a Deep Convolutional Structure

When using the electronic map, POI retrieval is the initial and importan...

Ji Zhao, et al. ∙

Jieping Ye

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