
-
Successive Projection for Solving Systems of Nonlinear Equations/Inequalities
Solving large-scale systems of nonlinear equations/inequalities is a fun...
read it
-
Selective Pseudo-Labeling with Reinforcement Learning for Semi-Supervised 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
-
Bi-Dimensional Feature Alignment for Cross-Domain Object Detection
Recently the problem of cross-domain object detection has started drawin...
read it
-
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...
read it
-
Robust Unsupervised Video Anomaly Detection by Multi-Path 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 Multi-Task 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 Node-Edge Co-evolution
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
-
Single-Timescale Stochastic Nonconvex-Concave Optimization for Smooth Nonlinear TD Learning
Temporal-Difference (TD) learning with nonlinear smooth function approxi...
read it
-
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...
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 Cross-Domain Few-Shot Learning with Unlabeled Data
Deep learning models are difficult to obtain good performance when data ...
read it
-
FMA-ETA: 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 Cross-Domain Few-Shot Classification
Deep learning models often require much annotated data to obtain good pe...
read it
-
Sequential Sentence Matching Network for Multi-turn Response Selection in Retrieval-based Chatbots
Recently, open domain multi-turn chatbots have attracted much interest f...
read it
-
Constructing Geographic and Long-term Temporal Graph for Traffic Forecasting
Traffic forecasting influences various intelligent transportation system...
read it
-
Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation
Contextual multi-armed bandit (MAB) achieves cutting-edge performance on...
read it
-
Mutual Learning Network for Multi-Source Domain Adaptation
Early Unsupervised Domain Adaptation (UDA) methods have mostly assumed t...
read it
-
Adaptive Object Detection with Dual Multi-Label Prediction
In this paper, we propose a novel end-to-end unsupervised deep domain ad...
read it
-
Augmented Parallel-Pyramid Net for Attention Guided Pose-Estimation
The target of human pose estimation is to determine body part or joint l...
read it
-
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...
read it
-
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...
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 Attention-based Graph Neural Network for Heterogeneous Structural Learning
In this paper, we focus on graph representation learning of heterogeneou...
read it
-
Deep Reinforcement Learning for Multi-Driver Vehicle Dispatching and Repositioning Problem
Order dispatching and driver repositioning (also known as fleet manageme...
read it
-
Building Effective Large-Scale Traffic State Prediction System: Traffic4cast Challenge Solution
How to build an effective large-scale traffic state prediction system is...
read it
-
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...
read it
-
Multi-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matching
Improving the efficiency of dispatching orders to vehicles is a research...
read it
-
Multi-grained Attention Networks for Single Image Super-Resolution
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 real-world human behaviors can be characterized as a sequential dec...
read it
-
AutoSlim: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates
Structured weight pruning is a representative model compression techniqu...
read it
-
AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates
Structured weight pruning is a representative model compression techniqu...
read it
-
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...
read it
-
Multi-Modal Graph Interaction for Multi-Graph 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 E-hailing 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^2-City: A Large-Scale 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 Ride-Sourcing Services with Multi-Agent Deep Reinforcement Learning
Ride-sourcing services are now reshaping the way people travel by effect...
read it
-
Efficient Ridesharing Order Dispatching with Mean Field Multi-Agent Reinforcement Learning
A fundamental question in any peer-to-peer 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 Spatio-Temporal Mining
In this paper, we develop a reinforcement learning (RL) based system to ...
read it
-
GESF: A Universal Discriminative Mapping Mechanism for Graph Representation Learning
Graph embedding is a central problem in social network analysis and many...
read it
-
Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction
Taxi demand prediction is an important building block to enabling intell...
read it