b'Jieping Ye'

Reinforcement Learning for Ridesharing: A Survey

In this paper, we present a comprehensive, in-depth survey of the litera...
05/03/2021 ∙ by Zhiwei Qin, et al. ∙ 0 ∙ share

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

We present a new practical framework based on deep reinforcement learnin...
03/08/2021 ∙ by Yan Jiao, et al. ∙ 0 ∙ share

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Successive Projection for Solving Systems of Nonlinear Equations/Inequalities

Solving large-scale systems of nonlinear equations/inequalities is a fun...
12/14/2020 ∙ by Wen-Jun Zeng, et al. ∙ 0 ∙ share

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

Recent domain adaptation methods have demonstrated impressive improvemen...
12/07/2020 ∙ by Bingyu Liu, et al. ∙ 0 ∙ share

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Domain Adaptation with Incomplete Target Domains

Domain adaptation, as a task of reducing the annotation cost in a target...
12/03/2020 ∙ by Zhenpeng Li, et al. ∙ 0 ∙ share

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Bi-Dimensional Feature Alignment for Cross-Domain Object Detection

Recently the problem of cross-domain object detection has started drawin...
11/14/2020 ∙ by Zhen Zhao, et al. ∙ 0 ∙ share

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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...
11/11/2020 ∙ by Jintao Ke, et al. ∙ 0 ∙ share

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Robust Unsupervised Video Anomaly Detection by Multi-Path Frame Prediction

Video anomaly detection is commonly used in many applications such as se...
11/05/2020 ∙ by Xuanzhao Wang, et al. ∙ 2 ∙ share

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DiDi's Machine Translation System for WMT2020

This paper describes DiDi AI Labs' submission to the WMT2020 news transl...
10/16/2020 ∙ by Tanfang Chen, et al. ∙ 0 ∙ share

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

While Deep Reinforcement Learning (DRL) has emerged as a promising appro...
10/15/2020 ∙ by Zhiyuan Xu, et al. ∙ 70 ∙ share

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

Graph neural networks have become an important tool for modeling structu...
10/09/2020 ∙ by Yucheng Lin, et al. ∙ 0 ∙ share

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Learning from Very Few Samples: A Survey

Few sample learning (FSL) is significant and challenging in the field of...
09/06/2020 ∙ by Jiang Lu, et al. ∙ 43 ∙ share

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

Temporal-Difference (TD) learning with nonlinear smooth function approxi...
08/23/2020 ∙ by Shuang Qiu, et al. ∙ 0 ∙ share

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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...
08/07/2020 ∙ by Teng Ye, et al. ∙ 0 ∙ share

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PropagationNet: Propagate Points to Curve to Learn Structure Information

Deep learning technique has dramatically boosted the performance of face...
06/25/2020 ∙ by Xiehe Huang, et al. ∙ 0 ∙ share

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Road Network Metric Learning for Estimated Time of Arrival

Recently, deep learning have achieved promising results in Estimated Tim...
06/24/2020 ∙ by Yiwen Sun, et al. ∙ 0 ∙ share

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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 ...
06/08/2020 ∙ by Zhen Zhao, et al. ∙ 0 ∙ share

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

Estimated time of arrival (ETA) is one of the most important services in...
06/07/2020 ∙ by Yiwen Sun, et al. ∙ 0 ∙ share

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Fusion Recurrent Neural Network

Considering deep sequence learning for practical application, two repres...
06/07/2020 ∙ by Yiwen Sun, et al. ∙ 0 ∙ share

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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...
05/18/2020 ∙ by Bingyu Liu, et al. ∙ 0 ∙ share

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

Recently, open domain multi-turn chatbots have attracted much interest f...
05/16/2020 ∙ by Chao Xiong, et al. ∙ 0 ∙ share

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Constructing Geographic and Long-term Temporal Graph for Traffic Forecasting

Traffic forecasting influences various intelligent transportation system...
04/23/2020 ∙ by Yiwen Sun, et al. ∙ 0 ∙ share

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Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation

Contextual multi-armed bandit (MAB) achieves cutting-edge performance on...
04/02/2020 ∙ by Mengyue Yang, et al. ∙ 0 ∙ share

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Mutual Learning Network for Multi-Source Domain Adaptation

Early Unsupervised Domain Adaptation (UDA) methods have mostly assumed t...
03/29/2020 ∙ by Zhenpeng Li, et al. ∙ 0 ∙ share

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Adaptive Object Detection with Dual Multi-Label Prediction

In this paper, we propose a novel end-to-end unsupervised deep domain ad...
03/29/2020 ∙ by Zhen Zhao, et al. ∙ 0 ∙ share

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Augmented Parallel-Pyramid Net for Attention Guided Pose-Estimation

The target of human pose estimation is to determine body part or joint l...
03/17/2020 ∙ by Luanxuan Hou, et al. ∙ 0 ∙ share

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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...
03/02/2020 ∙ by Shuang Qiu, et al. ∙ 0 ∙ share

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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...
02/05/2020 ∙ by Chengchun Shi, et al. ∙ 0 ∙ share

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

Generative adversarial networks (GANs) are a hot research topic recently...
01/20/2020 ∙ by Jie Gui, et al. ∙ 75 ∙ share

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An Attention-based Graph Neural Network for Heterogeneous Structural Learning

In this paper, we focus on graph representation learning of heterogeneou...
12/19/2019 ∙ by Huiting Hong, et al. ∙ 0 ∙ share

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

Order dispatching and driver repositioning (also known as fleet manageme...
11/25/2019 ∙ by John Holler, et al. ∙ 0 ∙ share

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

How to build an effective large-scale traffic state prediction system is...
11/11/2019 ∙ by Yang Liu, et al. ∙ 0 ∙ share

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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...
10/17/2019 ∙ by Jintao Ke, et al. ∙ 0 ∙ share

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

Improving the efficiency of dispatching orders to vehicles is a research...
10/07/2019 ∙ by Ming Zhou, et al. ∙ 0 ∙ share

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Multi-grained Attention Networks for Single Image Super-Resolution

Deep Convolutional Neural Networks (CNN) have drawn great attention in i...
09/26/2019 ∙ by Huapeng Wu, et al. ∙ 26 ∙ share

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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...
09/25/2019 ∙ by Shupeng Gui, et al. ∙ 0 ∙ share

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Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation

Reinforcement learning aims at searching the best policy model for decis...
07/12/2019 ∙ by Wenjie Shang, et al. ∙ 4 ∙ share

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Reward Advancement: Transforming Policy under Maximum Causal Entropy Principle

Many real-world human behaviors can be characterized as a sequential dec...
07/11/2019 ∙ by Guojun Wu, et al. ∙ 0 ∙ share

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

Structured weight pruning is a representative model compression techniqu...
07/06/2019 ∙ by Ning Liu, et al. ∙ 2 ∙ share

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

Structured weight pruning is a representative model compression techniqu...
07/06/2019 ∙ by Ning Liu, et al. ∙ 0 ∙ share

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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...
05/27/2019 ∙ by Jiarui Jin, et al. ∙ 0 ∙ share

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

Graph convolution network based approaches have been recently used to mo...
05/27/2019 ∙ by Xu Geng, et al. ∙ 2 ∙ share

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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...
05/23/2019 ∙ by Zhenyu Shou, et al. ∙ 0 ∙ share

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Object Detection in 20 Years: A Survey

Object detection, as of one the most fundamental and challenging problem...
05/13/2019 ∙ by Zhengxia Zou, et al. ∙ 0 ∙ share

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

Driving datasets accelerate the development of intelligent driving and r...
04/03/2019 ∙ by Zhengping Che, et al. ∙ 0 ∙ share

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POI Semantic Model with a Deep Convolutional Structure

When using the electronic map, POI retrieval is the initial and importan...
03/18/2019 ∙ by Ji Zhao, et al. ∙ 0 ∙ share

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Optimizing Online Matching for Ride-Sourcing Services with Multi-Agent Deep Reinforcement Learning

Ride-sourcing services are now reshaping the way people travel by effect...
02/17/2019 ∙ by Jintao Ke, et al. ∙ 0 ∙ share

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Efficient Ridesharing Order Dispatching with Mean Field Multi-Agent Reinforcement Learning

A fundamental question in any peer-to-peer ridesharing system is how to,...
01/31/2019 ∙ by Minne Li, et al. ∙ 0 ∙ share

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Which Factorization Machine Modeling is Better: A Theoretical Answer with Optimal Guarantee

Factorization machine (FM) is a popular machine learning model to captur...
01/30/2019 ∙ by Ming Lin, et al. ∙ 8 ∙ share

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Optimizing Taxi Carpool Policies via Reinforcement Learning and Spatio-Temporal Mining

In this paper, we develop a reinforcement learning (RL) based system to ...
11/11/2018 ∙ by Ishan Jindal, et al. ∙ 0 ∙ share

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Jieping Ye

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