
Successive Projection for Solving Systems of Nonlinear Equations/Inequalities
Solving largescale systems of nonlinear equations/inequalities is a fun...
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Selective PseudoLabeling with Reinforcement Learning for SemiSupervised Domain Adaptation
Recent domain adaptation methods have demonstrated impressive improvemen...
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Domain Adaptation with Incomplete Target Domains
Domain adaptation, as a task of reducing the annotation cost in a target...
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BiDimensional Feature Alignment for CrossDomain Object Detection
Recently the problem of crossdomain object detection has started drawin...
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Joint predictions of multimodal ridehailing demands: a deep multitask multigraph learningbased approach
Ridehailing platforms generally provide various service options to cust...
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Robust Unsupervised Video Anomaly Detection by MultiPath Frame Prediction
Video anomaly detection is commonly used in many applications such as se...
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DiDi's Machine Translation System for WMT2020
This paper describes DiDi AI Labs' submission to the WMT2020 news transl...
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Knowledge Transfer in MultiTask Deep Reinforcement Learning for Continuous Control
While Deep Reinforcement Learning (DRL) has emerged as a promising appro...
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Meta Graph Attention on Heterogeneous Graph with NodeEdge Coevolution
Graph neural networks have become an important tool for modeling structu...
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Learning from Very Few Samples: A Survey
Few sample learning (FSL) is significant and challenging in the field of...
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SingleTimescale Stochastic NonconvexConcave Optimization for Smooth Nonlinear TD Learning
TemporalDifference (TD) learning with nonlinear smooth function approxi...
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Predicting Individual Treatment Effects of Largescale Team Competitions in a Ridesharing Economy
Millions of drivers worldwide have enjoyed financial benefits and work s...
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PropagationNet: Propagate Points to Curve to Learn Structure Information
Deep learning technique has dramatically boosted the performance of face...
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Road Network Metric Learning for Estimated Time of Arrival
Recently, deep learning have achieved promising results in Estimated Tim...
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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 ...
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FMAETA: Estimating Travel Time Entirely Based on FFN With Attention
Estimated time of arrival (ETA) is one of the most important services in...
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Fusion Recurrent Neural Network
Considering deep sequence learning for practical application, two repres...
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Feature Transformation Ensemble Model with Batch Spectral Regularization for CrossDomain FewShot Classification
Deep learning models often require much annotated data to obtain good pe...
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Sequential Sentence Matching Network for Multiturn Response Selection in Retrievalbased Chatbots
Recently, open domain multiturn chatbots have attracted much interest f...
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Constructing Geographic and Longterm Temporal Graph for Traffic Forecasting
Traffic forecasting influences various intelligent transportation system...
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Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation
Contextual multiarmed bandit (MAB) achieves cuttingedge performance on...
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Mutual Learning Network for MultiSource Domain Adaptation
Early Unsupervised Domain Adaptation (UDA) methods have mostly assumed t...
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Adaptive Object Detection with Dual MultiLabel Prediction
In this paper, we propose a novel endtoend unsupervised deep domain ad...
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Augmented ParallelPyramid Net for Attention Guided PoseEstimation
The target of human pose estimation is to determine body part or joint l...
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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...
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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...
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A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications
Generative adversarial networks (GANs) are a hot research topic recently...
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An Attentionbased Graph Neural Network for Heterogeneous Structural Learning
In this paper, we focus on graph representation learning of heterogeneou...
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Deep Reinforcement Learning for MultiDriver Vehicle Dispatching and Repositioning Problem
Order dispatching and driver repositioning (also known as fleet manageme...
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Building Effective LargeScale Traffic State Prediction System: Traffic4cast Challenge Solution
How to build an effective largescale traffic state prediction system is...
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Predicting origindestination ridesourcing demand with a spatiotemporal encoderdecoder residual multigraph convolutional network
With the rapid development of mobileinternet technologies, ondemand ri...
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MultiAgent Reinforcement Learning for Orderdispatching via OrderVehicle Distribution Matching
Improving the efficiency of dispatching orders to vehicles is a research...
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Multigrained Attention Networks for Single Image SuperResolution
Deep Convolutional Neural Networks (CNN) have drawn great attention in i...
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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...
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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...
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Reward Advancement: Transforming Policy under Maximum Causal Entropy Principle
Many realworld human behaviors can be characterized as a sequential dec...
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AutoSlim: An Automatic DNN Structured Pruning Framework for UltraHigh Compression Rates
Structured weight pruning is a representative model compression techniqu...
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AutoCompress: An Automatic DNN Structured Pruning Framework for UltraHigh Compression Rates
Structured weight pruning is a representative model compression techniqu...
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CoRide: Joint Order Dispatching and Fleet Management for MultiScale RideHailing Platforms
How to optimally dispatch orders to vehicles and how to trade off betwee...
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MultiModal Graph Interaction for MultiGraph Convolution Network in Urban Spatiotemporal Forecasting
Graph convolution network based approaches have been recently used to mo...
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Where to Find Next Passengers on Ehailing Platforms?  A Markov Decision Process Approach
Vacant taxi drivers' passenger seeking process in a road network generat...
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Object Detection in 20 Years: A Survey
Object detection, as of one the most fundamental and challenging problem...
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D^2City: A LargeScale Dashcam Video Dataset of Diverse Traffic Scenarios
Driving datasets accelerate the development of intelligent driving and r...
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POI Semantic Model with a Deep Convolutional Structure
When using the electronic map, POI retrieval is the initial and importan...
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Optimizing Online Matching for RideSourcing Services with MultiAgent Deep Reinforcement Learning
Ridesourcing services are now reshaping the way people travel by effect...
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Efficient Ridesharing Order Dispatching with Mean Field MultiAgent Reinforcement Learning
A fundamental question in any peertopeer ridesharing system is how to,...
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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...
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Optimizing Taxi Carpool Policies via Reinforcement Learning and SpatioTemporal Mining
In this paper, we develop a reinforcement learning (RL) based system to ...
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GESF: A Universal Discriminative Mapping Mechanism for Graph Representation Learning
Graph embedding is a central problem in social network analysis and many...
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Deep MultiView SpatialTemporal Network for Taxi Demand Prediction
Taxi demand prediction is an important building block to enabling intell...
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Jieping Ye
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VP of Didi Research at Didi Chuxing, Associate Professor at University of Michigan