
Reinforcement Learning for Ridesharing: A Survey
In this paper, we present a comprehensive, indepth survey of the litera...
read it

Realworld Ridehailing Vehicle Repositioning using Deep Reinforcement Learning
We present a new practical framework based on deep reinforcement learnin...
read it

Successive Projection for Solving Systems of Nonlinear Equations/Inequalities
Solving largescale systems of nonlinear equations/inequalities is a fun...
read it

Selective PseudoLabeling with Reinforcement Learning for SemiSupervised Domain Adaptation
Recent domain adaptation methods have demonstrated impressive improvemen...
read it

Domain Adaptation with Incomplete Target Domains
Domain adaptation, as a task of reducing the annotation cost in a target...
read it

BiDimensional Feature Alignment for CrossDomain Object Detection
Recently the problem of crossdomain object detection has started drawin...
read it

Joint predictions of multimodal ridehailing demands: a deep multitask multigraph learningbased approach
Ridehailing platforms generally provide various service options to cust...
read it

Robust Unsupervised Video Anomaly Detection by MultiPath Frame Prediction
Video anomaly detection is commonly used in many applications such as se...
read it

DiDi's Machine Translation System for WMT2020
This paper describes DiDi AI Labs' submission to the WMT2020 news transl...
read it

Knowledge Transfer in MultiTask Deep Reinforcement Learning for Continuous Control
While Deep Reinforcement Learning (DRL) has emerged as a promising appro...
read it

Meta Graph Attention on Heterogeneous Graph with NodeEdge Coevolution
Graph neural networks have become an important tool for modeling structu...
read it

Learning from Very Few Samples: A Survey
Few sample learning (FSL) is significant and challenging in the field of...
read it

SingleTimescale Stochastic NonconvexConcave Optimization for Smooth Nonlinear TD Learning
TemporalDifference (TD) learning with nonlinear smooth function approxi...
read it

Predicting Individual Treatment Effects of Largescale Team Competitions in a Ridesharing Economy
Millions of drivers worldwide have enjoyed financial benefits and work s...
read it

PropagationNet: Propagate Points to Curve to Learn Structure Information
Deep learning technique has dramatically boosted the performance of face...
read it

Road Network Metric Learning for Estimated Time of Arrival
Recently, deep learning have achieved promising results in Estimated Tim...
read it

Ensemble Model with Batch Spectral Regularization and Data Blending for CrossDomain FewShot Learning with Unlabeled Data
Deep learning models are difficult to obtain good performance when data ...
read it

FMAETA: Estimating Travel Time Entirely Based on FFN With Attention
Estimated time of arrival (ETA) is one of the most important services in...
read it

Fusion Recurrent Neural Network
Considering deep sequence learning for practical application, two repres...
read it

Feature Transformation Ensemble Model with Batch Spectral Regularization for CrossDomain FewShot Classification
Deep learning models often require much annotated data to obtain good pe...
read it

Sequential Sentence Matching Network for Multiturn Response Selection in Retrievalbased Chatbots
Recently, open domain multiturn chatbots have attracted much interest f...
read it

Constructing Geographic and Longterm Temporal Graph for Traffic Forecasting
Traffic forecasting influences various intelligent transportation system...
read it

Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation
Contextual multiarmed bandit (MAB) achieves cuttingedge performance on...
read it

Mutual Learning Network for MultiSource Domain Adaptation
Early Unsupervised Domain Adaptation (UDA) methods have mostly assumed t...
read it

Adaptive Object Detection with Dual MultiLabel Prediction
In this paper, we propose a novel endtoend unsupervised deep domain ad...
read it

Augmented ParallelPyramid Net for Attention Guided PoseEstimation
The target of human pose estimation is to determine body part or joint l...
read it

Upper Confidence PrimalDual Optimization: Stochastically Constrained Markov Decision Processes with Adversarial Losses and Unknown Transitions
We consider online learning for episodic Markov decision processes (MDPs...
read it

A Reinforcement Learning Framework for TimeDependent Causal Effects Evaluation in A/B Testing
A/B testing, or online experiment is a standard business strategy to com...
read it

A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications
Generative adversarial networks (GANs) are a hot research topic recently...
read it

An Attentionbased Graph Neural Network for Heterogeneous Structural Learning
In this paper, we focus on graph representation learning of heterogeneou...
read it

Deep Reinforcement Learning for MultiDriver Vehicle Dispatching and Repositioning Problem
Order dispatching and driver repositioning (also known as fleet manageme...
read it

Building Effective LargeScale Traffic State Prediction System: Traffic4cast Challenge Solution
How to build an effective largescale traffic state prediction system is...
read it

Predicting origindestination ridesourcing demand with a spatiotemporal encoderdecoder residual multigraph convolutional network
With the rapid development of mobileinternet technologies, ondemand ri...
read it

MultiAgent Reinforcement Learning for Orderdispatching via OrderVehicle Distribution Matching
Improving the efficiency of dispatching orders to vehicles is a research...
read it

Multigrained Attention Networks for Single Image SuperResolution
Deep Convolutional Neural Networks (CNN) have drawn great attention in i...
read it

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...
read it

Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation
Reinforcement learning aims at searching the best policy model for decis...
read it

Reward Advancement: Transforming Policy under Maximum Causal Entropy Principle
Many realworld human behaviors can be characterized as a sequential dec...
read it

AutoSlim: An Automatic DNN Structured Pruning Framework for UltraHigh Compression Rates
Structured weight pruning is a representative model compression techniqu...
read it

AutoCompress: An Automatic DNN Structured Pruning Framework for UltraHigh Compression Rates
Structured weight pruning is a representative model compression techniqu...
read it

CoRide: Joint Order Dispatching and Fleet Management for MultiScale RideHailing Platforms
How to optimally dispatch orders to vehicles and how to trade off betwee...
read it

MultiModal Graph Interaction for MultiGraph Convolution Network in Urban Spatiotemporal Forecasting
Graph convolution network based approaches have been recently used to mo...
read it

Where to Find Next Passengers on Ehailing Platforms?  A Markov Decision Process Approach
Vacant taxi drivers' passenger seeking process in a road network generat...
read it

Object Detection in 20 Years: A Survey
Object detection, as of one the most fundamental and challenging problem...
read it

D^2City: A LargeScale Dashcam Video Dataset of Diverse Traffic Scenarios
Driving datasets accelerate the development of intelligent driving and r...
read it

POI Semantic Model with a Deep Convolutional Structure
When using the electronic map, POI retrieval is the initial and importan...
read it

Optimizing Online Matching for RideSourcing Services with MultiAgent Deep Reinforcement Learning
Ridesourcing services are now reshaping the way people travel by effect...
read it

Efficient Ridesharing Order Dispatching with Mean Field MultiAgent Reinforcement Learning
A fundamental question in any peertopeer ridesharing system is how to,...
read it

Which Factorization Machine Modeling is Better: A Theoretical Answer with Optimal Guarantee
Factorization machine (FM) is a popular machine learning model to captur...
read it

Optimizing Taxi Carpool Policies via Reinforcement Learning and SpatioTemporal Mining
In this paper, we develop a reinforcement learning (RL) based system to ...
read it
Jieping Ye
is this you? claim profile
VP of Didi Research at Didi Chuxing, Associate Professor at University of Michigan