b'Jieping Ye'

research

∙ 09/03/2023

A Survey on Service Route and Time Prediction in Instant Delivery: Taxonomy, Progress, and Prospects

Instant delivery services, such as food delivery and package delivery, h...

0 Haomin Wen, et al. ∙

research

∙ 07/28/2023

Uncertainty-aware Unsupervised Multi-Object Tracking

Without manually annotated identities, unsupervised multi-object tracker...

0 Kai Liu, et al. ∙

research

∙ 06/15/2023

Exploring the Application of Large-scale Pre-trained Models on Adverse Weather Removal

Image restoration under adverse weather conditions (e.g., rain, snow and...

0 Zhentao Tan, et al. ∙

research

∙ 05/18/2023

Ultra-High Resolution Segmentation with Ultra-Rich Context: A Novel Benchmark

With the increasing interest and rapid development of methods for Ultra-...

0 Deyi Ji, et al. ∙

research

∙ 05/12/2023

Self-Learning Symmetric Multi-view Probabilistic Clustering

Multi-view Clustering (MVC) has achieved significant progress, with many...

0 Junjie Liu, et al. ∙

research

∙ 03/08/2023

Semi-Supervised 2D Human Pose Estimation Driven by Position Inconsistency Pseudo Label Correction Module

In this paper, we delve into semi-supervised 2D human pose estimation. T...

0 Linzhi Huang, et al. ∙

research

∙ 03/06/2023

Towards Capacity-Aware Broker Matching: From Recommendation to Assignment

Online real estate platforms are gaining increasing popularity, where a ...

0 Shuyue Wei, et al. ∙

research

∙ 07/25/2022

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

While single-agent policy optimization in a fixed environment has attrac...

3 Shuang Qiu, et al. ∙

research

∙ 06/16/2022

ResNorm: Tackling Long-tailed Degree Distribution Issue in Graph Neural Networks via Normalization

Graph Neural Networks (GNNs) have attracted much attention due to their ...

0 Langzhang Liang, et al. ∙

research

∙ 06/12/2022

Stochastic Gradient Descent without Full Data Shuffle

Stochastic gradient descent (SGD) is the cornerstone of modern machine l...

39 Lijie Xu, et al. ∙

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...

0 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...

0 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...

0 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 ...

0 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...

0 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...

0 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...

0 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...

0 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...

0 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...

0 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...

0 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...

2 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...

0 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...

70 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...

0 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...

43 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...

0 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...

0 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...

0 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...

0 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 ...

0 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...

0 Yiwen Sun, et al. ∙

research

∙ 06/07/2020

Fusion Recurrent Neural Network

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

0 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...

0 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...

0 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...

0 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...

0 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...

0 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...

0 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...

0 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...

0 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...

0 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...

75 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...

0 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...

0 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...

0 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...

0 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...

0 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...

26 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...

0 Shupeng Gui, et al. ∙

Jieping Ye

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