Search Results for author: Xu Chen

Found 136 papers, 35 papers with code

Real-Time High-Resolution Pedestrian Detection in Crowded Scenes via Parallel Edge Offloading

no code implementations20 Jan 2023 Hao Wang, Hao Bao, Liekang Zeng, Ke Luo, Xu Chen

To identify dense and small-size pedestrians in surveillance systems, high-resolution cameras are widely deployed, where high-resolution images are captured and delivered to off-the-shelf pedestrian detection models.

Pedestrian Detection Scheduling

HiFlash: Communication-Efficient Hierarchical Federated Learning with Adaptive Staleness Control and Heterogeneity-aware Client-Edge Association

no code implementations16 Jan 2023 Qiong Wu, Xu Chen, Tao Ouyang, Zhi Zhou, Xiaoxi Zhang, Shusen Yang, Junshan Zhang

Federated learning (FL) is a promising paradigm that enables collaboratively learning a shared model across massive clients while keeping the training data locally.

Association Edge-computing +1

InstantAvatar: Learning Avatars from Monocular Video in 60 Seconds

no code implementations20 Dec 2022 Tianjian Jiang, Xu Chen, Jie Song, Otmar Hilliges

To achieve this efficiency we propose a carefully designed and engineered system, that leverages emerging acceleration structures for neural fields, in combination with an efficient empty space-skipping strategy for dynamic scenes.

Coarse-to-Fine Contrastive Learning on Graphs

no code implementations13 Dec 2022 Peiyao Zhao, Yuangang Pan, Xin Li, Xu Chen, Ivor W. Tsang, Lejian Liao

Inspired by the impressive success of contrastive learning (CL), a variety of graph augmentation strategies have been employed to learn node representations in a self-supervised manner.

Contrastive Learning Learning-To-Rank

Proximal Gradient-Based Unfolding for Massive Random Access in IoT Networks

no code implementations4 Dec 2022 Yinan Zou, Yong Zhou, Xu Chen, Yonina C. Eldar

Simulations show that the proposed unfolding neural network achieves better recovery performance, convergence rate, and adaptivity than current baselines.

Action Detection Activity Detection +1

Olive Branch Learning: A Topology-Aware Federated Learning Framework for Space-Air-Ground Integrated Network

no code implementations2 Dec 2022 Qingze Fang, Zhiwei Zhai, Shuai Yu, Qiong Wu, Xiaowen Gong, Xu Chen

The space-air-ground integrated network (SAGIN), one of the key technologies for next-generation mobile communication systems, can facilitate data transmission for users all over the world, especially in some remote areas where vast amounts of informative data are collected by Internet of remote things (IoRT) devices to support various data-driven artificial intelligence (AI) services.

Federated Learning

Recent Advances in RecBole: Extensions with more Practical Considerations

1 code implementation28 Nov 2022 Lanling Xu, Zhen Tian, Gaowei Zhang, Lei Wang, Junjie Zhang, Bowen Zheng, YiFan Li, Yupeng Hou, Xingyu Pan, Yushuo Chen, Wayne Xin Zhao, Xu Chen, Ji-Rong Wen

In order to show the recent update in RecBole, we write this technical report to introduce our latest improvements on RecBole.

Fast-SNARF: A Fast Deformer for Articulated Neural Fields

1 code implementation28 Nov 2022 Xu Chen, Tianjian Jiang, Jie Song, Max Rietmann, Andreas Geiger, Michael J. Black, Otmar Hilliges

A key challenge in making such methods applicable to articulated objects, such as the human body, is to model the deformation of 3D locations between the rest pose (a canonical space) and the deformed space.

3D Reconstruction Novel View Synthesis

Truthful Transaction Protocol for E-Commerce Networks Based on Double Auction

no code implementations IEEE Transactions on Network Science and Engineering 2022 Jiachen Sun, Ning Ge, Xu Chen, Wei Feng, Jianhua Lu

This screening algorithm is customer-oriented and offers personalized commodities by preventing unqualified sellers from participating in the transaction.

GNN at the Edge: Cost-Efficient Graph Neural Network Processing over Distributed Edge Servers

no code implementations31 Oct 2022 Liekang Zeng, Chongyu Yang, Peng Huang, Zhi Zhou, Shuai Yu, Xu Chen

Edge intelligence has arisen as a promising computing paradigm for supporting miscellaneous smart applications that rely on machine learning techniques.

Miscellaneous Scheduling

Recommendation with User Active Disclosing Willingness

no code implementations25 Oct 2022 Lei Wang, Xu Chen, Quanyu Dai, Zhenhua Dong

Recommender system has been deployed in a large amount of real-world applications, profoundly influencing people's daily life and production. Traditional recommender models mostly collect as comprehensive as possible user behaviors for accurate preference estimation.

Recommendation Systems

Multi-Modal Experience Inspired AI Creation

1 code implementation2 Sep 2022 Qian Cao, Xu Chen, Ruihua Song, Hao Jiang, Guang Yang, Zhao Cao

To model such human capabilities, in this paper, we define and solve a novel AI creation problem based on human experiences.

Text Generation

Debiased Recommendation with Neural Stratification

no code implementations15 Aug 2022 Quanyu Dai, Zhenhua Dong, Xu Chen

Debiased recommender models have recently attracted increasing attention from the academic and industry communities.

Neural Message Passing for Visual Relationship Detection

1 code implementation8 Aug 2022 Yue Hu, Siheng Chen, Xu Chen, Ya zhang, Xiao Gu

Visual relationship detection aims to detect the interactions between objects in an image; however, this task suffers from combinatorial explosion due to the variety of objects and interactions.

Visual Relationship Detection

Collaboration in Participant-Centric Federated Learning: A Game-Theoretical Perspective

no code implementations25 Jul 2022 Guangjing Huang, Xu Chen, Tao Ouyang, Qian Ma, Lin Chen, Junshan Zhang

To coordinate the selfish and heterogeneous participants, we propose a novel analytic framework for incentivizing effective and efficient collaborations for participant-centric FL.

Federated Learning

RecBole 2.0: Towards a More Up-to-Date Recommendation Library

2 code implementations15 Jun 2022 Wayne Xin Zhao, Yupeng Hou, Xingyu Pan, Chen Yang, Zeyu Zhang, Zihan Lin, Jingsen Zhang, Shuqing Bian, Jiakai Tang, Wenqi Sun, Yushuo Chen, Lanling Xu, Gaowei Zhang, Zhen Tian, Changxin Tian, Shanlei Mu, Xinyan Fan, Xu Chen, Ji-Rong Wen

In order to support the study of recent advances in recommender systems, this paper presents an extended recommendation library consisting of eight packages for up-to-date topics and architectures.

Data Augmentation Fairness +2

GraphAD: A Graph Neural Network for Entity-Wise Multivariate Time-Series Anomaly Detection

no code implementations23 May 2022 Xu Chen, Qiu Qiu, Changshan Li, Kunqing Xie

We also construct a real-world entity-wise multivariate time-series dataset from the business data of Ele. me.

Anomaly Detection Management +1

Working memory inspired hierarchical video decomposition with transformative representations

1 code implementation21 Apr 2022 Binjie Qin, Haohao Mao, Ruipeng Zhang, Yueqi Zhu, Song Ding, Xu Chen

Video decomposition is very important to extract moving foreground objects from complex backgrounds in computer vision, machine learning, and medical imaging, e. g., extracting moving contrast-filled vessels from the complex and noisy backgrounds of X-ray coronary angiography (XCA).

Retrieval

Robust PCA Unrolling Network for Super-resolution Vessel Extraction in X-ray Coronary Angiography

no code implementations16 Apr 2022 Binjie Qin, Haohao Mao, Yiming Liu, Jun Zhao, Yisong Lv, Yueqi Zhu, Song Ding, Xu Chen

Although robust PCA has been increasingly adopted to extract vessels from X-ray coronary angiography (XCA) images, challenging problems such as inefficient vessel-sparsity modelling, noisy and dynamic background artefacts, and high computational cost still remain unsolved.

Super-Resolution

Reinforcement Re-ranking with 2D Grid-based Recommendation Panels

no code implementations11 Apr 2022 Sirui Chen, Xiao Zhang, Xu Chen, Zhiyu Li, YuAn Wang, Quan Lin, Jun Xu

Presenting items in grid-based result panels poses new challenges to recommender systems because existing models are all designed to output sequential lists while the slots in a grid-based panel have no explicit order.

Recommendation Systems Re-Ranking

Sequential Recommendation with User Evolving Preference Decomposition

no code implementations31 Mar 2022 Weiqi Shao, Xu Chen, Long Xia, Jiashu Zhao, Dawei Yin

To solve this problem, in this paper, we propose a novel sequential recommender model via decomposing and modeling user independent preferences.

Sequential Recommendation

Knowledge-Guided Learning for Transceiver Design in Over-the-Air Federated Learning

no code implementations28 Mar 2022 Yinan Zou, Zixin Wang, Xu Chen, Haibo Zhou, Yong Zhou

Based on the convergence analysis, we formulate an optimization problem to minimize the upper bound to enhance the learning performance, followed by proposing an alternating optimization algorithm to facilitate the optimal transceiver design for AirComp-assisted FL.

Federated Learning

A Unified Network Equilibrium for E-Hailing Platform Operation and Customer Mode Choice

no code implementations9 Mar 2022 Xu Chen, Xuan Di

This paper aims to combine both economic and network user equilibrium for ride-sourcing and ride-pooling services, while endogenously optimizing the pooling sequence of two origin-destination (OD) pairs.

3D Dense Face Alignment with Fused Features by Aggregating CNNs and GCNs

no code implementations9 Mar 2022 Yanda Meng, Xu Chen, Dongxu Gao, Yitian Zhao, Xiaoyun Yang, Yihong Qiao, Xiaowei Huang, Yalin Zheng

In this paper, we propose a novel multi-level aggregation network to regress the coordinates of the vertices of a 3D face from a single 2D image in an end-to-end manner.

3D Face Alignment 3D Face Reconstruction +1

Generalizable Information Theoretic Causal Representation

no code implementations17 Feb 2022 Mengyue Yang, Xinyu Cai, Furui Liu, Xu Chen, Zhitang Chen, Jianye Hao, Jun Wang

It is evidence that representation learning can improve model's performance over multiple downstream tasks in many real-world scenarios, such as image classification and recommender systems.

Image Classification Recommendation Systems +1

Measuring "Why" in Recommender Systems: a Comprehensive Survey on the Evaluation of Explainable Recommendation

no code implementations14 Feb 2022 Xu Chen, Yongfeng Zhang, Ji-Rong Wen

Beyond summarizing the previous work, we also analyze the (dis)advantages of existing evaluation methods and provide a series of guidelines on how to select them.

Explainable Recommendation Recommendation Systems

Action Keypoint Network for Efficient Video Recognition

no code implementations17 Jan 2022 Xu Chen, Yahong Han, Xiaohan Wang, Yifan Sun, Yi Yang

An effective approach is to select informative content from the holistic video, yielding a popular family of dynamic video recognition methods.

Action Recognition Point Cloud Classification +1

Debiased Recommendation with User Feature Balancing

no code implementations16 Jan 2022 Mengyue Yang, Guohao Cai, Furui Liu, Zhenhua Dong, Xiuqiang He, Jianye Hao, Jun Wang, Xu Chen

To alleviate these problems, in this paper, we propose a novel debiased recommendation framework based on user feature balancing.

Causal Inference Recommendation Systems

Learning to Identify Top Elo Ratings: A Dueling Bandits Approach

1 code implementation12 Jan 2022 Xue Yan, Yali Du, Binxin Ru, Jun Wang, Haifeng Zhang, Xu Chen

The Elo rating system is widely adopted to evaluate the skills of (chess) game and sports players.

Scheduling

gDNA: Towards Generative Detailed Neural Avatars

no code implementations CVPR 2022 Xu Chen, Tianjian Jiang, Jie Song, Jinlong Yang, Michael J. Black, Andreas Geiger, Otmar Hilliges

Furthermore, we show that our method can be used on the task of fitting human models to raw scans, outperforming the previous state-of-the-art.

Edge Robotics: Edge-Computing-Accelerated Multi-Robot Simultaneous Localization and Mapping

no code implementations25 Dec 2021 Peng Huang, Liekang Zeng, Xu Chen, Ke Luo, Zhi Zhou, Shuai Yu

With the wide penetration of smart robots in multifarious fields, Simultaneous Localization and Mapping (SLAM) technique in robotics has attracted growing attention in the community.

Edge-computing Simultaneous Localization and Mapping

D-HAN: Dynamic News Recommendation with Hierarchical Attention Network

1 code implementation19 Dec 2021 Qinghua Zhao, Xu Chen, HUI ZHANG, Shuai Ma

However, in real-world scenarios, the news can be quite complex and diverse, blindly squeezing all the contents into an embedding vector can be less effective in extracting information compatible with the personalized preference of the users.

News Recommendation

I M Avatar: Implicit Morphable Head Avatars from Videos

1 code implementation CVPR 2022 Yufeng Zheng, Victoria Fernández Abrevaya, Marcel C. Bühler, Xu Chen, Michael J. Black, Otmar Hilliges

Traditional 3D morphable face models (3DMMs) provide fine-grained control over expression but cannot easily capture geometric and appearance details.

Gumble Softmax For User Behavior Modeling

no code implementations6 Dec 2021 Weiqi Shao, Xu Chen, Jiashu Zhao, Long Xia, Dawei Yin

We propose a sequential model with dynamic number of representations for recommendation systems (RDRSR).

Sequential Recommendation

User behavior understanding in real world settings

no code implementations6 Dec 2021 Weiqi Shao, Xu Chen, Jiashu Zhao, Long Xia, Dawei Yin

It is necessary to learn a dynamic group of representations according the item groups in a user historical behavior.

Learning Proximal Operator Methods for Massive Connectivity in IoT Networks

no code implementations6 Dec 2021 Yinan Zou, Yong Zhou, Yuanming Shi, Xu Chen

To mitigate all the aforementioned limitations, we in this paper develop an effective unfolding neural network framework built upon the proximal operator method to tackle the JADCE problem in IoT networks, where the base station is equipped with multiple antennas.

Action Detection Activity Detection

Source Free Unsupervised Graph Domain Adaptation

no code implementations2 Dec 2021 Haitao Mao, Lun Du, Yujia Zheng, Qiang Fu, Zelin Li, Xu Chen, Shi Han, Dongmei Zhang

They utilize labels from the source domain as the supervision signal and are jointly trained on both the source graph and the target graph.

Domain Adaptation Node Classification

Neuron with Steady Response Leads to Better Generalization

no code implementations30 Nov 2021 Qiang Fu, Lun Du, Haitao Mao, Xu Chen, Wei Fang, Shi Han, Dongmei Zhang

Based on the analysis results, we articulate the Neuron Steadiness Hypothesis: the neuron with similar responses to instances of the same class leads to better generalization.

Inductive Bias

Human Performance Capture from Monocular Video in the Wild

no code implementations29 Nov 2021 Chen Guo, Xu Chen, Jie Song, Otmar Hilliges

In this work, we propose a method capable of capturing the dynamic 3D human shape from a monocular video featuring challenging body poses, without any additional input.

3D Human Shape Estimation Autonomous Driving

Inhomogeneous Social Recommendation with Hypergraph Convolutional Networks

1 code implementation5 Nov 2021 Zirui Zhu, Chen Gao, Xu Chen, Nian Li, Depeng Jin, Yong Li

With the hypergraph convolutional networks, the social relations can be modeled in a more fine-grained manner, which more accurately depicts real users' preferences, and benefits the recommendation performance.

Render In-between: Motion Guided Video Synthesis for Action Interpolation

no code implementations1 Nov 2021 Hsuan-I Ho, Xu Chen, Jie Song, Otmar Hilliges

We propose to address these issues in a motion-guided frame-upsampling framework that is capable of producing realistic human motion and appearance.

Neural Rendering

SkullEngine: A Multi-stage CNN Framework for Collaborative CBCT Image Segmentation and Landmark Detection

no code implementations7 Oct 2021 Qin Liu, Han Deng, Chunfeng Lian, Xiaoyang Chen, Deqiang Xiao, Lei Ma, Xu Chen, Tianshu Kuang, Jaime Gateno, Pew-Thian Yap, James J. Xia

We propose a multi-stage coarse-to-fine CNN-based framework, called SkullEngine, for high-resolution segmentation and large-scale landmark detection through a collaborative, integrated, and scalable JSD model and three segmentation and landmark detection refinement models.

Image Segmentation Semantic Segmentation

Robust Cross-Modal Semi-supervised Few Shot Learning

no code implementations29 Sep 2021 Xu Chen

Semi-supervised learning has been successfully applied to few-shot learning (FSL) due to its capability of leveraging the information of limited labeled data and massive unlabeled data.

Few-Shot Learning

Informative Robust Causal Representation for Generalizable Deep Learning

no code implementations29 Sep 2021 Mengyue Yang, Furui Liu, Xu Chen, Zhitang Chen, Jianye Hao, Jun Wang

In many real-world scenarios, such as image classification and recommender systems, it is evidence that representation learning can improve model's performance over multiple downstream tasks.

Image Classification Recommendation Systems +1

Top-N Recommendation with Counterfactual User Preference Simulation

no code implementations2 Sep 2021 Mengyue Yang, Quanyu Dai, Zhenhua Dong, Xu Chen, Xiuqiang He, Jun Wang

To alleviate this problem, in this paper, we propose to reformulate the recommendation task within the causal inference framework, which enables us to counterfactually simulate user ranking-based preferences to handle the data scarce problem.

Causal Inference Recommendation Systems

Counterfactual Explainable Recommendation

2 code implementations24 Aug 2021 Juntao Tan, Shuyuan Xu, Yingqiang Ge, Yunqi Li, Xu Chen, Yongfeng Zhang

Technically, for each item recommended to each user, CountER formulates a joint optimization problem to generate minimal changes on the item aspects so as to create a counterfactual item, such that the recommendation decision on the counterfactual item is reversed.

Causal Inference Counterfactual Explanation +3

Neuron Campaign for Initialization Guided by Information Bottleneck Theory

1 code implementation14 Aug 2021 Haitao Mao, Xu Chen, Qiang Fu, Lun Du, Shi Han, Dongmei Zhang

Initialization plays a critical role in the training of deep neural networks (DNN).

Enabling Long-Term Cooperation in Cross-Silo Federated Learning: A Repeated Game Perspective

no code implementations22 Jun 2021 Ning Zhang, Qian Ma, Xu Chen

We show that enforced by a punishment strategy, such a cooperative strategy is a subgame perfect Nash equilibrium (SPNE) of the infinitely repeated game, under which some clients who are free riders at the NE of the stage game choose to be (partial) contributors.

Federated Learning

HifiFace: 3D Shape and Semantic Prior Guided High Fidelity Face Swapping

1 code implementation18 Jun 2021 YuHan Wang, Xu Chen, Junwei Zhu, Wenqing Chu, Ying Tai, Chengjie Wang, Jilin Li, Yongjian Wu, Feiyue Huang, Rongrong Ji

In this work, we propose a high fidelity face swapping method, called HifiFace, which can well preserve the face shape of the source face and generate photo-realistic results.

3D Face Reconstruction Face Recognition +1

A Game-Theoretic Approach to Multi-Agent Trust Region Optimization

1 code implementation12 Jun 2021 Ying Wen, Hui Chen, Yaodong Yang, Zheng Tian, Minne Li, Xu Chen, Jun Wang

Trust region methods are widely applied in single-agent reinforcement learning problems due to their monotonic performance-improvement guarantee at every iteration.

Atari Games Multi-agent Reinforcement Learning +2

TrafficStream: A Streaming Traffic Flow Forecasting Framework Based on Graph Neural Networks and Continual Learning

1 code implementation11 Jun 2021 Xu Chen, Junshan Wang, Kunqing Xie

With the rapid growth of traffic sensors deployed, a massive amount of traffic flow data are collected, revealing the long-term evolution of traffic flows and the gradual expansion of traffic networks.

Continual Learning

TabularNet: A Neural Network Architecture for Understanding Semantic Structures of Tabular Data

no code implementations6 Jun 2021 Lun Du, Fei Gao, Xu Chen, Ran Jia, Junshan Wang, Jiang Zhang, Shi Han, Dongmei Zhang

To simultaneously extract spatial and relational information from tables, we propose a novel neural network architecture, TabularNet.

graph construction

Understanding and Improvement of Adversarial Training for Network Embedding from an Optimization Perspective

no code implementations17 May 2021 Lun Du, Xu Chen, Fei Gao, Kunqing Xie, Shi Han, Dongmei Zhang

Network Embedding aims to learn a function mapping the nodes to Euclidean space contribute to multiple learning analysis tasks on networks.

Link Prediction Network Embedding +1

Contrastive Attraction and Contrastive Repulsion for Representation Learning

no code implementations8 May 2021 Huangjie Zheng, Xu Chen, Jiangchao Yao, Hongxia Yang, Chunyuan Li, Ya zhang, Hao Zhang, Ivor Tsang, Jingren Zhou, Mingyuan Zhou

We realize this strategy with contrastive attraction and contrastive repulsion (CACR), which makes the query not only exert a greater force to attract more distant positive samples but also do so to repel closer negative samples.

Contrastive Learning Representation Learning

SNARF: Differentiable Forward Skinning for Animating Non-Rigid Neural Implicit Shapes

1 code implementation ICCV 2021 Xu Chen, Yufeng Zheng, Michael J. Black, Otmar Hilliges, Andreas Geiger

However, this is problematic since the backward warp field is pose dependent and thus requires large amounts of data to learn.

Generating Multi-scale Maps from Remote Sensing Images via Series Generative Adversarial Networks

no code implementations31 Mar 2021 Xu Chen, Bangguo Yin, Songqiang Chen, Haifeng Li, Tian Xu

The series strategy avoids RS-m inconsistency as inputs are high-resolution large-scale RSIs, and reduces the distribution gap in multi-scale map generation through similar pixel distributions among multi-scale maps.

Image-to-Image Translation Translation

Large-scale simultaneous inference under dependence

no code implementations22 Feb 2021 Jinjin Tian, Xu Chen, Eugene Katsevich, Jelle Goeman, Aaditya Ramdas

Simultaneous inference allows for the exploration of data while deciding on criteria for proclaiming discoveries.

Statistics Theory Methodology Statistics Theory

Causal Collaborative Filtering

1 code implementation3 Feb 2021 Shuyuan Xu, Yingqiang Ge, Yunqi Li, Zuohui Fu, Xu Chen, Yongfeng Zhang

In this paper, we propose Causal Collaborative Filtering (CCF) -- a general framework for modeling causality in collaborative filtering and recommendation.

Collaborative Filtering Recommendation Systems

Deep Reinforcement Learning with Spatio-temporal Traffic Forecasting for Data-Driven Base Station Sleep Control

no code implementations21 Jan 2021 Qiong Wu, Xu Chen, Zhi Zhou, Liang Chen, Junshan Zhang

To meet the ever increasing mobile traffic demand in 5G era, base stations (BSs) have been densely deployed in radio access networks (RANs) to increase the network coverage and capacity.

EC-SAGINs: Edge Computing-enhanced Space-Air-Ground Integrated Networks for Internet of Vehicles

no code implementations15 Jan 2021 Shuai Yu, Xiaowen Gong, Qian Shi, Xiaofei Wang, Xu Chen

After discussing several existing orbital and aerial edge computing architectures, we propose a framework of edge computing-enabled space-air-ground integrated networks (EC-SAGINs) to support various IoV services for the vehicles in remote areas.

Edge-computing Imitation Learning +1

Discrete Knowledge Graph Embedding based on Discrete Optimization

no code implementations13 Jan 2021 Yunqi Li, Shuyuan Xu, Bo Liu, Zuohui Fu, Shuchang Liu, Xu Chen, Yongfeng Zhang

This paper proposes a discrete knowledge graph (KG) embedding (DKGE) method, which projects KG entities and relations into the Hamming space based on a computationally tractable discrete optimization algorithm, to solve the formidable storage and computation cost challenges in traditional continuous graph embedding methods.

Knowledge Graph Embedding

Generate Natural Language Explanations for Recommendation

no code implementations9 Jan 2021 Hanxiong Chen, Xu Chen, Shaoyun Shi, Yongfeng Zhang

Motivated by this problem, we propose to generate free-text natural language explanations for personalized recommendation.

Denoising Explainable Recommendation +2

Multi-Agent Trust Region Learning

1 code implementation1 Jan 2021 Ying Wen, Hui Chen, Yaodong Yang, Zheng Tian, Minne Li, Xu Chen, Jun Wang

We derive the lower bound of agents' payoff improvements for MATRL methods, and also prove the convergence of our method on the meta-game fixed points.

Atari Games Multi-agent Reinforcement Learning +3

Causal World Models by Unsupervised Deconfounding of Physical Dynamics

no code implementations28 Dec 2020 Minne Li, Mengyue Yang, Furui Liu, Xu Chen, Zhitang Chen, Jun Wang

The capability of imagining internally with a mental model of the world is vitally important for human cognition.

Dynamic driving and routing games for autonomous vehicles on networks: A mean field game approach

no code implementations15 Dec 2020 Kuang Huang, Xu Chen, Xuan Di, Qiang Du

In this paper, we aim to develop a game-theoretic model to solve for AVs's optimal driving strategies of velocity control in the interior of a road link and route choice at a junction node.

Autonomous Vehicles Decision Making Optimization and Control Systems and Control Systems and Control

FedHome: Cloud-Edge based Personalized Federated Learning for In-Home Health Monitoring

1 code implementation14 Dec 2020 Qiong Wu, Xu Chen, Zhi Zhou, Junshan Zhang

In this paper, we propose FedHome, a novel cloud-edge based federated learning framework for in-home health monitoring, which learns a shared global model in the cloud from multiple homes at the network edges and achieves data privacy protection by keeping user data locally.

Human Activity Recognition Personalized Federated Learning

CoEdge: Cooperative DNN Inference with Adaptive Workload Partitioning over Heterogeneous Edge Devices

no code implementations6 Dec 2020 Liekang Zeng, Xu Chen, Zhi Zhou, Lei Yang, Junshan Zhang

CoEdge utilizes available computation and communication resources at the edge and dynamically partitions the DNN inference workload adaptive to devices' computing capabilities and network conditions.

TSSRGCN: Temporal Spectral Spatial Retrieval Graph Convolutional Network for Traffic Flow Forecasting

no code implementations30 Nov 2020 Xu Chen, Yuanxing Zhang, Lun Du, Zheng Fang, Yi Ren, Kaigui Bian, Kunqing Xie

Further analysis indicates that the locality and globality of the traffic networks are critical to traffic flow prediction and the proposed TSSRGCN model can adapt to the various temporal traffic patterns.

Retrieval

Multi-Agent Reinforcement Learning for Markov Routing Games: A New Modeling Paradigm For Dynamic Traffic Assignment

no code implementations22 Nov 2020 Zhenyu Shou, Xu Chen, Yongjie Fu, Xuan Di

We show that the routing behavior of intelligent agents is shown to converge to the classical notion of predictive dynamic user equilibrium (DUE) when traffic environments are simulated using dynamic loading models (DNL).

Autonomous Vehicles Bilevel Optimization +2

RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms

1 code implementation3 Nov 2020 Wayne Xin Zhao, Shanlei Mu, Yupeng Hou, Zihan Lin, Yushuo Chen, Xingyu Pan, Kaiyuan Li, Yujie Lu, Hui Wang, Changxin Tian, Yingqian Min, Zhichao Feng, Xinyan Fan, Xu Chen, Pengfei Wang, Wendi Ji, Yaliang Li, Xiaoling Wang, Ji-Rong Wen

In this library, we implement 73 recommendation models on 28 benchmark datasets, covering the categories of general recommendation, sequential recommendation, context-aware recommendation and knowledge-based recommendation.

Collaborative Filtering Sequential Recommendation

GAIN: Graph Attention & Interaction Network for Inductive Semi-Supervised Learning over Large-scale Graphs

no code implementations3 Nov 2020 Yunpeng Weng, Xu Chen, Liang Chen, Wei Liu

Most existing GNN models exploit a single type of aggregator (e. g., mean-pooling) to aggregate neighboring nodes information, and then add or concatenate the output of aggregator to the current representation vector of the center node.

Graph Attention Link Prediction +1

Learning on Attribute-Missing Graphs

3 code implementations3 Nov 2020 Xu Chen, Siheng Chen, Jiangchao Yao, Huangjie Zheng, Ya zhang, Ivor W Tsang

Thereby, designing a new GNN for these graphs is a burning issue to the graph learning community.

Graph Learning Link Prediction

Learning Euler's Elastica Model for Medical Image Segmentation

1 code implementation1 Nov 2020 Xu Chen, Xiangde Luo, Yitian Zhao, Shaoting Zhang, Guotai Wang, Yalin Zheng

Inspired by Euler's Elastica model and recent active contour models introduced into the field of deep learning, we propose a novel active contour with elastica (ACE) loss function incorporating Elastica (curvature and length) and region information as geometrically-natural constraints for the image segmentation tasks.

Image Segmentation Medical Image Segmentation +1

CAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable Recommendation

1 code implementation29 Oct 2020 Yikun Xian, Zuohui Fu, Handong Zhao, Yingqiang Ge, Xu Chen, Qiaoying Huang, Shijie Geng, Zhou Qin, Gerard de Melo, S. Muthukrishnan, Yongfeng Zhang

User profiles can capture prominent user behaviors from the history, and provide valuable signals about which kinds of path patterns are more likely to lead to potential items of interest for the user.

Explainable Recommendation Knowledge Graphs +1

Learning to Match Jobs with Resumes from Sparse Interaction Data using Multi-View Co-Teaching Network

no code implementations25 Sep 2020 Shuqing Bian, Xu Chen, Wayne Xin Zhao, Kun Zhou, Yupeng Hou, Yang song, Tao Zhang, Ji-Rong Wen

Compared with pure text-based matching models, the proposed approach is able to learn better data representations from limited or even sparse interaction data, which is more resistible to noise in training data.

Text Matching

When Deep Reinforcement Learning Meets Federated Learning: Intelligent Multi-Timescale Resource Management for Multi-access Edge Computing in 5G Ultra Dense Network

no code implementations22 Sep 2020 Shuai Yu, Xu Chen, Zhi Zhou, Xiaowen Gong, Di wu

Ultra-dense edge computing (UDEC) has great potential, especially in the 5G era, but it still faces challenges in its current solutions, such as the lack of: i) efficient utilization of multiple 5G resources (e. g., computation, communication, storage and service resources); ii) low overhead offloading decision making and resource allocation strategies; and iii) privacy and security protection schemes.

Decision Making Edge-computing +2

Decoupled Variational Embedding for Signed Directed Networks

1 code implementation28 Aug 2020 Xu Chen, Jiangchao Yao, Maosen Li, Ya zhang, Yan-Feng Wang

Comprehensive results on both link sign prediction and node recommendation task demonstrate the effectiveness of DVE.

Link Sign Prediction Node Classification +1

Learning Robust Node Representations on Graphs

no code implementations26 Aug 2020 Xu Chen, Ya zhang, Ivor Tsang, Yuangang Pan

Graph neural networks (GNN), as a popular methodology for node representation learning on graphs, currently mainly focus on preserving the smoothness and identifiability of node representations.

Contrastive Learning Representation Learning

Category Level Object Pose Estimation via Neural Analysis-by-Synthesis

no code implementations ECCV 2020 Xu Chen, Zijian Dong, Jie Song, Andreas Geiger, Otmar Hilliges

Many object pose estimation algorithms rely on the analysis-by-synthesis framework which requires explicit representations of individual object instances.

Image Generation Pose Estimation

Collaborative Adversarial Learning for RelationalLearning on Multiple Bipartite Graphs

no code implementations16 Jul 2020 Jingchao Su, Xu Chen, Ya zhang, Siheng Chen, Dan Lv, Chenyang Li

The two-level alignment acts as two different constraints on different relations of the shared entities and facilitates better knowledge transfer for relational learning on multiple bipartite graphs.

Relational Reasoning Transfer Learning

Joint Multi-User DNN Partitioning and Computational Resource Allocation for Collaborative Edge Intelligence

no code implementations15 Jul 2020 Xin Tang, Xu Chen, Liekang Zeng, Shuai Yu, Lin Chen

With the assistance of edge servers, user equipments (UEs) are able to run deep neural network (DNN) based AI applications, which are generally resource-hungry and compute-intensive, such that an individual UE can hardly afford by itself in real time.

Edge-computing

Learning Post-Hoc Causal Explanations for Recommendation

no code implementations30 Jun 2020 Shuyuan Xu, Yunqi Li, Shuchang Liu, Zuohui Fu, Xu Chen, Yongfeng Zhang

State-of-the-art recommender systems have the ability to generate high-quality recommendations, but usually cannot provide intuitive explanations to humans due to the usage of black-box prediction models.

Association Sequential Recommendation

Network Massive MIMO Transmission Over Millimeter-Wave and Terahertz Bands: Mobility Enhancement and Blockage Mitigation

no code implementations6 May 2020 Li You, Xu Chen, Xiaohang Song, Fan Jiang, Wenjin Wang, Xiqi Gao, Gerhard Fettweis

Based on these insights, the network massive MIMO precoding design is reduced to a network sum-rate maximization problem with respect to beam domain power allocation.

Knowledge Distillation for Mobile Edge Computation Offloading

no code implementations9 Apr 2020 Haowei Chen, Liekang Zeng, Shuai Yu, Xu Chen

In this article, we propose an edge computation offloading framework based on Deep Imitation Learning (DIL) and Knowledge Distillation (KD), which assists end devices to quickly make fine-grained decisions to optimize the delay of computation tasks online.

Imitation Learning Knowledge Distillation +1

XBlock-EOS: Extracting and Exploring Blockchain Data From EOSIO

no code implementations26 Mar 2020 Weilin Zheng, Zibin Zheng, Hong-Ning Dai, Xu Chen, PeiLin Zheng

It is challenging to process and analyze a high volume of raw EOSIO data and establish the mapping from original raw data to the well-grained datasets since it requires substantial efforts in extracting various types of data as well as sophisticated knowledge on software engineering and data analytics.

Computational Engineering, Finance, and Science Cryptography and Security

HierTrain: Fast Hierarchical Edge AI Learning with Hybrid Parallelism in Mobile-Edge-Cloud Computing

no code implementations22 Mar 2020 Deyin Liu, Xu Chen, Zhi Zhou, Qing Ling

We develop a novel \textit{hybrid parallelism} method, which is the key to HierTrain, to adaptively assign the DNN model layers and the data samples across the three levels of edge device, edge server and cloud center.

Scheduling

DeepCP: Deep Learning Driven Cascade Prediction Based Autonomous Content Placement in Closed Social Network

no code implementations9 Mar 2020 Qiong Wu, Muhong Wu, Xu Chen, Zhi Zhou, Kaiwen He, Liang Chen

Accordingly, we further propose a novel autonomous content placement mechanism CP-GAN which adopts the generative adversarial network (GAN) for agile placement decision making to reduce the content access latency and enhance users' QoE.

Decision Making

HFEL: Joint Edge Association and Resource Allocation for Cost-Efficient Hierarchical Federated Edge Learning

no code implementations26 Feb 2020 Siqi Luo, Xu Chen, Qiong Wu, Zhi Zhou, Shuai Yu

We further formulate a joint computation and communication resource allocation and edge association problem for device users under HFEL framework to achieve global cost minimization.

Distributed, Parallel, and Cluster Computing

Personalized Federated Learning for Intelligent IoT Applications: A Cloud-Edge based Framework

no code implementations25 Feb 2020 Qiong Wu, Kaiwen He, Xu Chen

Internet of Things (IoT) have widely penetrated in different aspects of modern life and many intelligent IoT services and applications are emerging.

Edge-computing Human Activity Recognition +1

Liability Design for Autonomous Vehicles and Human-Driven Vehicles: A Hierarchical Game-Theoretic Approach

no code implementations5 Nov 2019 Xuan Di, Xu Chen, Eric Talley

The game is then simulated with numerical examples to investigate the emergence of human drivers' moral hazard, the AV manufacturer's role in traffic safety, and the law maker's role in liability design.

Autonomous Driving

Cascading: Association Augmented Sequential Recommendation

no code implementations17 Oct 2019 Xu Chen, Kenan Cui, Ya zhang, Yan-Feng Wang

Recently, recommendation according to sequential user behaviors has shown promising results in many application scenarios.

Association Graph Embedding +1

Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing

no code implementations4 Oct 2019 En Li, Liekang Zeng, Zhi Zhou, Xu Chen

As a key technology of enabling Artificial Intelligence (AI) applications in 5G era, Deep Neural Networks (DNNs) have quickly attracted widespread attention.

Change Point Detection Edge-computing

Node Attribute Generation on Graphs

3 code implementations23 Jul 2019 Xu Chen, Siheng Chen, Huangjie Zheng, Jiangchao Yao, Kenan Cui, Ya zhang, Ivor W. Tsang

NANG learns a unifying latent representation which is shared by both node attributes and graph structures and can be translated to different modalities.

Data Augmentation General Classification +2

Convergence of Edge Computing and Deep Learning: A Comprehensive Survey

1 code implementation19 Jul 2019 Xiaofei Wang, Yiwen Han, Victor C. M. Leung, Dusit Niyato, Xueqiang Yan, Xu Chen

Ubiquitous sensors and smart devices from factories and communities are generating massive amounts of data, and ever-increasing computing power is driving the core of computation and services from the cloud to the edge of the network.

Edge-computing Face Recognition +1

A Survey on Neural Machine Reading Comprehension

no code implementations10 Jun 2019 Boyu Qiu, Xu Chen, Jungang Xu, Yingfei Sun

Enabling a machine to read and comprehend the natural language documents so that it can answer some questions remains an elusive challenge.

Machine Reading Comprehension

Learning Active Contour Models for Medical Image Segmentation

no code implementations CVPR 2019 Xu Chen, Bryan M. Williams, Srinivasa R. Vallabhaneni, Gabriela Czanner, Rachel Williams, Yalin Zheng

Our aim was to tackle this limitation by developing a new model based on deep learning which takes into account the area inside as well as outside the region of interest as well as the size of boundaries during learning.

Image Segmentation Medical Image Segmentation +1

Visually-aware Recommendation with Aesthetic Features

no code implementations2 May 2019 Wenhui Yu, Xiangnan He, Jian Pei, Xu Chen, Li Xiong, Jinfei Liu, Zheng Qin

While recent developments on visually-aware recommender systems have taken the product image into account, none of them has considered the aesthetic aspect.

Decision Making Recommendation Systems +1

Unpaired Pose Guided Human Image Generation

1 code implementation8 Jan 2019 Xu Chen, Jie Song, Otmar Hilliges

This paper studies the task of full generative modelling of realistic images of humans, guided only by coarse sketch of the pose, while providing control over the specific instance or type of outfit worn by the user.

Image-to-Image Translation Translation

Monocular Neural Image Based Rendering with Continuous View Control

2 code implementations ICCV 2019 Xu Chen, Jie Song, Otmar Hilliges

The approach is self-supervised and only requires 2D images and associated view transforms for training.

Novel View Synthesis

Ramp-based Twin Support Vector Clustering

no code implementations10 Dec 2018 Zhen Wang, Xu Chen, Chun-Na Li, Yuan-Hai Shao

Traditional plane-based clustering methods measure the cost of within-cluster and between-cluster by quadratic, linear or some other unbounded functions, which may amplify the impact of cost.

Robust Active Learning for Electrocardiographic Signal Classification

no code implementations21 Nov 2018 Xu Chen, Saratendu Sethi

The classification of electrocardiographic (ECG) signals is a challenging problem for healthcare industry.

Active Learning Classification +1

Variational Collaborative Learning for User Probabilistic Representation

no code implementations22 Sep 2018 Kenan Cui, Xu Chen, Jiangchao Yao, Ya zhang

Conventional CF-based methods use the user-item interaction data as the sole information source to recommend items to users.

Collaborative Filtering Recommendation Systems

In-Edge AI: Intelligentizing Mobile Edge Computing, Caching and Communication by Federated Learning

no code implementations19 Sep 2018 Xiaofei Wang, Yiwen Han, Chenyang Wang, Qiyang Zhao, Xu Chen, Min Chen

In order to bring more intelligence to the edge systems, compared to traditional optimization methodology, and driven by the current deep learning techniques, we propose to integrate the Deep Reinforcement Learning techniques and Federated Learning framework with the mobile edge systems, for optimizing the mobile edge computing, caching and communication.

Edge-computing Federated Learning

Aesthetic-based Clothing Recommendation

no code implementations16 Sep 2018 Wenhui Yu, Huidi Zhang, Xiangnan He, Xu Chen, Li Xiong, Zheng Qin

Considering that the aesthetic preference varies significantly from user to user and by time, we then propose a new tensor factorization model to incorporate the aesthetic features in a personalized manner.

Recommendation Systems

Follow Me at the Edge: Mobility-Aware Dynamic Service Placement for Mobile Edge Computing

no code implementations14 Sep 2018 Tao Ouyang, Zhi Zhou, Xu Chen

To address this challenge in terms of the performance-cost trade-off, in this paper we study the mobile edge service performance optimization problem under long-term cost budget constraint.

Edge-computing

Edge Intelligence: On-Demand Deep Learning Model Co-Inference with Device-Edge Synergy

no code implementations20 Jun 2018 En Li, Zhi Zhou, Xu Chen

As the backbone technology of machine learning, deep neural networks (DNNs) have have quickly ascended to the spotlight.

Topology Control for Energy-Efficient Localization in Mobile Underwater Sensor Networks using Stackelberg Game

no code implementations31 May 2018 Yali Yuan, Chencheng Liang, Megumi Kaneko, Xu Chen, Dieter Hogrefe

In this game, the sensor node acts as a leader taking into account factors such as 'two-hop' anchor nodes and energy consumption, while anchor nodes act as multiple followers, considering their ability to localize sensor nodes and their energy consumption.

Networking and Internet Architecture

Learning Heterogeneous Knowledge Base Embeddings for Explainable Recommendation

4 code implementations9 May 2018 Qingyao Ai, Vahid Azizi, Xu Chen, Yongfeng Zhang

Specifically, we propose a knowledge-base representation learning framework to embed heterogeneous entities for recommendation, and based on the embedded knowledge base, a soft matching algorithm is proposed to generate personalized explanations for the recommended items.

Collaborative Filtering Explainable Recommendation +3

Explainable Recommendation: A Survey and New Perspectives

no code implementations30 Apr 2018 Yongfeng Zhang, Xu Chen

In this survey, we provide a comprehensive review for the explainable recommendation research.

Explainable Recommendation Product Recommendation +1

Fictitious GAN: Training GANs with Historical Models

1 code implementation ECCV 2018 Hao Ge, Yin Xia, Xu Chen, Randall Berry, Ying Wu

Inspired by the fictitious play learning process, a novel training method, referred to as Fictitious GAN, is introduced.

Superposition-Assisted Stochastic Optimization for Hawkes Processes

no code implementations13 Feb 2018 Hongteng Xu, Xu Chen, Lawrence Carin

We consider the learning of multi-agent Hawkes processes, a model containing multiple Hawkes processes with shared endogenous impact functions and different exogenous intensities.

Sequential Recommendation Stochastic Optimization

Training Generative Adversarial Networks via Primal-Dual Subgradient Methods: A Lagrangian Perspective on GAN

no code implementations ICLR 2018 Xu Chen, Jiang Wang, Hao Ge

This formulation shows the connection between the standard GAN training process and the primal-dual subgradient methods for convex optimization.

Visually Explainable Recommendation

no code implementations31 Jan 2018 Xu Chen, Yongfeng Zhang, Hongteng Xu, Yixin Cao, Zheng Qin, Hongyuan Zha

By this, we can not only provide recommendation results to the users, but also tell the users why an item is recommended by providing intuitive visual highlights in a personalized manner.

Explainable Recommendation Recommendation Systems

Texture Object Segmentation Based on Affine Invariant Texture Detection

no code implementations23 Dec 2017 Jianwei Zhang, Xu Chen, Xuezhong Xiao

To solve the issue of segmenting rich texture images, a novel detection methods based on the affine invariable principle is proposed.

Edge Detection Semantic Segmentation

Benefits from Superposed Hawkes Processes

no code implementations14 Oct 2017 Hongteng Xu, Dixin Luo, Xu Chen, Lawrence Carin

The superposition of Hawkes processes is demonstrated to be beneficial for tightening the upper bound of excess risk under certain conditions, and we show the feasibility of the benefit in typical situations.

Point Processes Recommendation Systems

Feedback-Controlled Sequential Lasso Screening

no code implementations21 Aug 2016 Yun Wang, Xu Chen, Peter J. Ramadge

In this context, we propose and explore a feedback controlled sequential screening scheme.

Model Selection

Multi-lingual Geoparsing based on Machine Translation

no code implementations6 Nov 2015 Xu Chen, Han Zhang, Judith Gelernter

Our results for geoparsing Chinese and Arabic text using our multi-lingual geoparsing method are comparable to our results for geoparsing English text with our English tools.

Machine Translation Translation

Deep Haar Scattering Networks

no code implementations30 Sep 2015 Xiuyuan Cheng, Xu Chen, Stephane Mallat

An orthogonal Haar scattering transform is a deep network, computed with a hierarchy of additions, subtractions and absolute values, over pairs of coefficients.

Classification General Classification

Unsupervised Deep Haar Scattering on Graphs

no code implementations NeurIPS 2014 Xu Chen, Xiuyuan Cheng, Stéphane Mallat

The classification of high-dimensional data defined on graphs is particularly difficult when the graph geometry is unknown.

Classification Dimensionality Reduction +1

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