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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...
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07/28/2023
Uncertainty-aware Unsupervised Multi-Object Tracking
Without manually annotated identities, unsupervised multi-object tracker...
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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...
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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-...
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05/12/2023
Self-Learning Symmetric Multi-view Probabilistic Clustering
Multi-view Clustering (MVC) has achieved significant progress, with many...
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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...
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03/06/2023
Towards Capacity-Aware Broker Matching: From Recommendation to Assignment
Online real estate platforms are gaining increasing popularity, where a ...
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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...
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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 ...
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06/12/2022
Stochastic Gradient Descent without Full Data Shuffle
Stochastic gradient descent (SGD) is the cornerstone of modern machine l...
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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...
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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...
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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...
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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 ...
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05/03/2021
Reinforcement Learning for Ridesharing: A Survey
In this paper, we present a comprehensive, in-depth survey of the litera...
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03/08/2021
Real-world Ride-hailing Vehicle Repositioning using Deep Reinforcement Learning
We present a new practical framework based on deep reinforcement learnin...
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12/14/2020
Successive Projection for Solving Systems of Nonlinear Equations/Inequalities
Solving large-scale systems of nonlinear equations/inequalities is a fun...
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12/07/2020
Selective Pseudo-Labeling with Reinforcement Learning for Semi-Supervised Domain Adaptation
Recent domain adaptation methods have demonstrated impressive improvemen...
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12/03/2020
Domain Adaptation with Incomplete Target Domains
Domain adaptation, as a task of reducing the annotation cost in a target...
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11/14/2020
Bi-Dimensional Feature Alignment for Cross-Domain Object Detection
Recently the problem of cross-domain object detection has started drawin...
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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...
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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...
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10/16/2020
DiDi's Machine Translation System for WMT2020
This paper describes DiDi AI Labs' submission to the WMT2020 news transl...
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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...
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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...
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09/06/2020
Learning from Very Few Samples: A Survey
Few sample learning (FSL) is significant and challenging in the field of...
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08/23/2020
Single-Timescale Stochastic Nonconvex-Concave Optimization for Smooth Nonlinear TD Learning
Temporal-Difference (TD) learning with nonlinear smooth function approxi...
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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...
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06/25/2020
PropagationNet: Propagate Points to Curve to Learn Structure Information
Deep learning technique has dramatically boosted the performance of face...
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06/24/2020
Road Network Metric Learning for Estimated Time of Arrival
Recently, deep learning have achieved promising results in Estimated Tim...
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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 ...
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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...
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06/07/2020
Fusion Recurrent Neural Network
Considering deep sequence learning for practical application, two repres...
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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...
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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...
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04/23/2020
Constructing Geographic and Long-term Temporal Graph for Traffic Forecasting
Traffic forecasting influences various intelligent transportation system...
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04/02/2020
Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation
Contextual multi-armed bandit (MAB) achieves cutting-edge performance on...
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03/29/2020
Mutual Learning Network for Multi-Source Domain Adaptation
Early Unsupervised Domain Adaptation (UDA) methods have mostly assumed t...
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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...
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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...
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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...
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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...
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01/20/2020
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications
Generative adversarial networks (GANs) are a hot research topic recently...
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12/19/2019
An Attention-based Graph Neural Network for Heterogeneous Structural Learning
In this paper, we focus on graph representation learning of heterogeneou...
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11/25/2019
Deep Reinforcement Learning for Multi-Driver Vehicle Dispatching and Repositioning Problem
Order dispatching and driver repositioning (also known as fleet manageme...
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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...
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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...
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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...
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09/26/2019
Multi-grained Attention Networks for Single Image Super-Resolution
Deep Convolutional Neural Networks (CNN) have drawn great attention in i...
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09/25/2019
