Search Results for author: Xu Chen

Found 202 papers, 62 papers with code

Design and Optimization of Hierarchical Gradient Coding for Distributed Learning at Edge Devices

no code implementations16 Jun 2024 Weiheng Tang, Jingyi Li, Lin Chen, Xu Chen

In this paper, along a different line, we investigate the problem of mitigating the straggler effect in hierarchical distributed learning systems with an additional layer composed of edge nodes.


IMFL-AIGC: Incentive Mechanism Design for Federated Learning Empowered by Artificial Intelligence Generated Content

no code implementations12 Jun 2024 Guangjing Huang, Qiong Wu, Jingyi Li, Xu Chen

Federated learning (FL) has emerged as a promising paradigm that enables clients to collaboratively train a shared global model without uploading their local data.

Federated Learning

Galaxy: A Resource-Efficient Collaborative Edge AI System for In-situ Transformer Inference

no code implementations27 May 2024 Shengyuan Ye, Jiangsu Du, Liekang Zeng, Wenzhong Ou, Xiaowen Chu, Yutong Lu, Xu Chen

Transformer-based models have unlocked a plethora of powerful intelligent applications at the edge, such as voice assistant in smart home.

Collaborative Inference

Attaining Human`s Desirable Outcomes in Human-AI Interaction via Structural Causal Games

no code implementations26 May 2024 Anjie Liu, Jianhong Wang, Haoxuan Li, Xu Chen, Jun Wang, Samuel Kaski, Mengyue Yang

In human-AI interaction, a prominent goal is to attain human`s desirable outcome with the assistance of AI agents, which can be ideally delineated as a problem of seeking the optimal Nash Equilibrium that matches the human`s desirable outcome.

Are Long-LLMs A Necessity For Long-Context Tasks?

no code implementations24 May 2024 Hongjin Qian, Zheng Liu, Peitian Zhang, Kelong Mao, Yujia Zhou, Xu Chen, Zhicheng Dou

The learning and deployment of long-LLMs remains a challenging problem despite recent progresses.

Revisiting Counterfactual Regression through the Lens of Gromov-Wasserstein Information Bottleneck

1 code implementation24 May 2024 Hao Yang, Zexu Sun, Hongteng Xu, Xu Chen

However, the selection bias between control and treatment groups often imbalances the two groups' latent distributions and negatively impacts this method's performance.

counterfactual regression +1

Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and Attribute Control

no code implementations21 May 2024 Yue Han, Junwei Zhu, Keke He, Xu Chen, Yanhao Ge, Wei Li, Xiangtai Li, Jiangning Zhang, Chengjie Wang, Yong liu

We observe that both face reenactment/swapping tasks essentially involve combinations of target structure, ID and attribute.

Attribute Decoder +1

Generalizing Knowledge Graph Embedding with Universal Orthogonal Parameterization

1 code implementation14 May 2024 Rui Li, Chaozhuo Li, Yanming Shen, Zeyu Zhang, Xu Chen

Recent advances in knowledge graph embedding (KGE) rely on Euclidean/hyperbolic orthogonal relation transformations to model intrinsic logical patterns and topological structures.

Knowledge Graph Embedding Knowledge Graphs

Graphon Mean Field Games with a Representative Player: Analysis and Learning Algorithm

no code implementations8 May 2024 Fuzhong Zhou, Chenyu Zhang, Xu Chen, Xuan Di

We propose a discrete time graphon game formulation on continuous state and action spaces using a representative player to study stochastic games with heterogeneous interaction among agents.

A Single Online Agent Can Efficiently Learn Mean Field Games

no code implementations5 May 2024 Chenyu Zhang, Xu Chen, Xuan Di

Mean field games (MFGs) are a promising framework for modeling the behavior of large-population systems.

STT: Stateful Tracking with Transformers for Autonomous Driving

no code implementations30 Apr 2024 Longlong Jing, Ruichi Yu, Xu Chen, Zhengli Zhao, Shiwei Sheng, Colin Graber, Qi Chen, Qinru Li, Shangxuan Wu, Han Deng, Sangjin Lee, Chris Sweeney, Qiurui He, Wei-Chih Hung, Tong He, Xingyi Zhou, Farshid Moussavi, Zijian Guo, Yin Zhou, Mingxing Tan, Weilong Yang, CongCong Li

In this paper, we propose STT, a Stateful Tracking model built with Transformers, that can consistently track objects in the scenes while also predicting their states accurately.

Autonomous Driving

Debiased Collaborative Filtering with Kernel-Based Causal Balancing

1 code implementation30 Apr 2024 Haoxuan Li, Chunyuan Zheng, Yanghao Xiao, Peng Wu, Zhi Geng, Xu Chen, Peng Cui

Inspired by these gaps, we propose to approximate the balancing functions in reproducing kernel Hilbert space and demonstrate that, based on the universal property and representer theorem of kernel functions, the causal balancing constraints can be better satisfied.

Collaborative Filtering

Implementation of Big AI Models for Wireless Networks with Collaborative Edge Computing

no code implementations27 Apr 2024 Liekang Zeng, Shengyuan Ye, Xu Chen, Yang Yang

Motivated by this, in this article, we propose collaborative edge training, a novel training mechanism that orchestrates a group of trusted edge devices as a resource pool for expedited, sustainable big AI model training at the edge.

Edge-computing Scheduling

A Survey on the Memory Mechanism of Large Language Model based Agents

1 code implementation21 Apr 2024 Zeyu Zhang, Xiaohe Bo, Chen Ma, Rui Li, Xu Chen, Quanyu Dai, Jieming Zhu, Zhenhua Dong, Ji-Rong Wen

Compared with original LLMs, LLM-based agents are featured in their self-evolving capability, which is the basis for solving real-world problems that need long-term and complex agent-environment interactions.

Language Modelling Large Language Model

Single-temporal Supervised Remote Change Detection for Domain Generalization

no code implementations17 Apr 2024 Qiangang Du, Jinlong Peng, Xu Chen, Qingdong He, Liren He, Qiang Nie, Wenbing Zhu, Mingmin Chi, Yabiao Wang, Chengjie Wang

In this paper, we propose a multimodal contrastive learning (ChangeCLIP) based on visual-language pre-training for change detection domain generalization.

Change Detection Contrastive Learning +1

Cramer-Rao Bounds for Near-Field Sensing: A Generic Modular Architecture

no code implementations11 Apr 2024 Chunwei Meng, Dingyou Ma, Xu Chen, Zhiyong Feng, Yuanwei Liu

A generic modular array architecture is proposed, featuring uniform/non-uniform subarray layouts that allows for flexible deployment.

RecGPT: Generative Personalized Prompts for Sequential Recommendation via ChatGPT Training Paradigm

no code implementations6 Apr 2024 Yabin Zhang, Wenhui Yu, Erhan Zhang, Xu Chen, Lantao Hu, Peng Jiang, Kun Gai

For the model part, we adopt Generative Pre-training Transformer (GPT) as the sequential recommendation model and design a user modular to capture personalized information.

Natural Language Understanding Sequential Recommendation

DMAD: Dual Memory Bank for Real-World Anomaly Detection

no code implementations19 Mar 2024 Jianlong Hu, Xu Chen, Zhenye Gan, Jinlong Peng, Shengchuan Zhang, Jiangning Zhang, Yabiao Wang, Chengjie Wang, Liujuan Cao, Rongrong Ji

To address the challenge of real-world anomaly detection, we propose a new framework named Dual Memory bank enhanced representation learning for Anomaly Detection (DMAD).

Anomaly Detection Representation Learning

Multiply Robust Estimation for Local Distribution Shifts with Multiple Domains

1 code implementation21 Feb 2024 Steven Wilkins-Reeves, Xu Chen, Qi Ma, Christine Agarwal, Aude Hofleitner

We focus on scenarios where data distributions vary across multiple segments of the entire population and only make local assumptions about the differences between training and test (deployment) distributions within each segment.

Large Language Model-based Human-Agent Collaboration for Complex Task Solving

1 code implementation20 Feb 2024 Xueyang Feng, Zhi-Yuan Chen, Yujia Qin, Yankai Lin, Xu Chen, Zhiyuan Liu, Ji-Rong Wen

We construct a human-agent collaboration dataset to train this policy model in an offline reinforcement learning environment.

Language Modelling Large Language Model +1

DMCE: Diffusion Model Channel Enhancer for Multi-User Semantic Communication Systems

no code implementations29 Jan 2024 Youcheng Zeng, Xinxin He, Xu Chen, Haonan Tong, Zhaohui Yang, Yijun Guo, Jianjun Hao

To address this, this paper proposes a diffusion model (DM)-based channel enhancer (DMCE) for improving the performance of multi-user semantic communication, with the DM learning the particular data distribution of channel effects on the transmitted semantic features.

Semantic Communication Semantic Segmentation

Efficient Online Crowdsourcing with Complex Annotations

no code implementations25 Jan 2024 Reshef Meir, Viet-An Nguyen, Xu Chen, Jagdish Ramakrishnan, Udi Weinsberg

Crowdsourcing platforms use various truth discovery algorithms to aggregate annotations from multiple labelers.

M$^3$TN: Multi-gate Mixture-of-Experts based Multi-valued Treatment Network for Uplift Modeling

no code implementations24 Jan 2024 Zexu Sun, Xu Chen

M$^3$TN consists of two components: 1) a feature representation module with Multi-gate Mixture-of-Experts to improve the efficiency; 2) a reparameterization module by modeling uplift explicitly to improve the effectiveness.

TAROT: A Hierarchical Framework with Multitask Co-Pretraining on Semi-Structured Data towards Effective Person-Job Fit

no code implementations15 Jan 2024 Yihan Cao, Xu Chen, Lun Du, Hao Chen, Qiang Fu, Shi Han, Yushu Du, Yanbin Kang, Guangming Lu, Zi Li

Person-job fit is an essential part of online recruitment platforms in serving various downstream applications like Job Search and Candidate Recommendation.

Text2Analysis: A Benchmark of Table Question Answering with Advanced Data Analysis and Unclear Queries

no code implementations21 Dec 2023 Xinyi He, Mengyu Zhou, Xinrun Xu, Xiaojun Ma, Rui Ding, Lun Du, Yan Gao, Ran Jia, Xu Chen, Shi Han, Zejian yuan, Dongmei Zhang

We evaluate five state-of-the-art models using three different metrics and the results show that our benchmark presents introduces considerable challenge in the field of tabular data analysis, paving the way for more advanced research opportunities.

Question Answering

Professional Network Matters: Connections Empower Person-Job Fit

no code implementations19 Dec 2023 Hao Chen, Lun Du, Yuxuan Lu, Qiang Fu, Xu Chen, Shi Han, Yanbin Kang, Guangming Lu, Zi Li

Online recruitment platforms typically employ Person-Job Fit models in the core service that automatically match suitable job seekers with appropriate job positions.

Graph Neural Network

Spatial Deep Learning for Site-Specific Movement Optimization of Aerial Base Stations

no code implementations16 Dec 2023 Jiangbin Lyu, Xu Chen, Jiefeng Zhang, Liqun Fu

Unmanned aerial vehicles (UAVs) can be utilized as aerial base stations (ABSs) to provide wireless connectivity for ground users (GUs) in various emergency scenarios.

Turbo: Informativity-Driven Acceleration Plug-In for Vision-Language Models

no code implementations12 Dec 2023 Chen Ju, Haicheng Wang, Zeqian Li, Xu Chen, Zhonghua Zhai, Weilin Huang, Shuai Xiao

Vision-Language Large Models (VLMs) have become primary backbone of AI, due to the impressive performance.

AnomalyDiffusion: Few-Shot Anomaly Image Generation with Diffusion Model

1 code implementation10 Dec 2023 Teng Hu, Jiangning Zhang, Ran Yi, Yuzhen Du, Xu Chen, Liang Liu, Yabiao Wang, Chengjie Wang

Existing anomaly inspection methods are limited in their performance due to insufficient anomaly data.

Image Generation

HOLD: Category-agnostic 3D Reconstruction of Interacting Hands and Objects from Video

1 code implementation CVPR 2024 Zicong Fan, Maria Parelli, Maria Eleni Kadoglou, Muhammed Kocabas, Xu Chen, Michael J. Black, Otmar Hilliges

Since humans interact with diverse objects every day, the holistic 3D capture of these interactions is important to understand and model human behaviour.

3D Reconstruction Object +1

Enhancing Cross-domain Click-Through Rate Prediction via Explicit Feature Augmentation

no code implementations30 Nov 2023 Xu Chen, Zida Cheng, Jiangchao Yao, Chen Ju, Weilin Huang, Jinsong Lan, Xiaoyi Zeng, Shuai Xiao

Later the augmentation network employs the explicit cross-domain knowledge as augmented information to boost the target domain CTR prediction.

Click-Through Rate Prediction Transfer Learning

Don't Make Your LLM an Evaluation Benchmark Cheater

no code implementations3 Nov 2023 Kun Zhou, Yutao Zhu, Zhipeng Chen, Wentong Chen, Wayne Xin Zhao, Xu Chen, Yankai Lin, Ji-Rong Wen, Jiawei Han

Large language models~(LLMs) have greatly advanced the frontiers of artificial intelligence, attaining remarkable improvement in model capacity.

DYNAMITE: Dynamic Interplay of Mini-Batch Size and Aggregation Frequency for Federated Learning with Static and Streaming Dataset

no code implementations20 Oct 2023 Weijie Liu, Xiaoxi Zhang, Jingpu Duan, Carlee Joe-Wong, Zhi Zhou, Xu Chen

Federated Learning (FL) is a distributed learning paradigm that can coordinate heterogeneous edge devices to perform model training without sharing private data.

Federated Learning Navigate

TRANSOM: An Efficient Fault-Tolerant System for Training LLMs

1 code implementation16 Oct 2023 Baodong Wu, Lei Xia, Qingping Li, Kangyu Li, Xu Chen, Yongqiang Guo, Tieyao Xiang, YuHeng Chen, Shigang Li

As a result, A substantial amount of training time is devoted to task checkpoint saving and loading, task rescheduling and restart, and task manual anomaly checks, which greatly harms the overall training efficiency.

Anomaly Detection

Fine-Grained Annotation for Face Anti-Spoofing

no code implementations12 Oct 2023 Xu Chen, Yunde Jia, Yuwei Wu

In this paper, we propose a fine-grained annotation method for face anti-spoofing.

Face Anti-Spoofing Segmentation

Integrated Sensing and Communication Neighbor Discovery for MANET with Gossip Mechanism

no code implementations11 Oct 2023 Zhiqing Wei, Chenfei Li, Yanpeng Cui, Xu Chen, Zeyang Meng, Zhiyong Feng

In order to further reduce the convergence time of ND, this paper introduces the ISAC-enabled gossip mechanism into the ND algorithm.


Text-to-Image Generation for Abstract Concepts

no code implementations26 Sep 2023 Jiayi Liao, Xu Chen, Qiang Fu, Lun Du, Xiangnan He, Xiang Wang, Shi Han, Dongmei Zhang

Recent years have witnessed the substantial progress of large-scale models across various domains, such as natural language processing and computer vision, facilitating the expression of concrete concepts.

Text-to-Image Generation

Phasic Content Fusing Diffusion Model with Directional Distribution Consistency for Few-Shot Model Adaption

1 code implementation ICCV 2023 Teng Hu, Jiangning Zhang, Liang Liu, Ran Yi, Siqi Kou, Haokun Zhu, Xu Chen, Yabiao Wang, Chengjie Wang, Lizhuang Ma

To address these problems, we propose a novel phasic content fusing few-shot diffusion model with directional distribution consistency loss, which targets different learning objectives at distinct training stages of the diffusion model.

Domain Adaptation

Roulette: A Semantic Privacy-Preserving Device-Edge Collaborative Inference Framework for Deep Learning Classification Tasks

no code implementations6 Sep 2023 Jingyi Li, Guocheng Liao, Lin Chen, Xu Chen

In this paper, we propose a framework of Roulette, which is a task-oriented semantic privacy-preserving collaborative inference framework for deep learning classifiers.

Collaborative Inference Privacy Preserving +1

FedDD: Toward Communication-efficient Federated Learning with Differential Parameter Dropout

no code implementations31 Aug 2023 Zhiying Feng, Xu Chen, Qiong Wu, Wen Wu, Xiaoxi Zhang, Qianyi Huang

FedDD consists of two key modules: dropout rate allocation and uploaded parameter selection, which will optimize the model parameter uploading ratios tailored to different clients' heterogeneous conditions and also select the proper set of important model parameters for uploading subject to clients' dropout rate constraints.

Federated Learning

ViCo: Engaging Video Comment Generation with Human Preference Rewards

no code implementations22 Aug 2023 Yuchong Sun, Bei Liu, Xu Chen, Ruihua Song, Jianlong Fu

Experiments on ViCo-20k show that the comments generated by our ViCo model exhibit the best performance in terms of both quantitative and qualitative results, particularly when engagement is considered.

Caption Generation Comment Generation +1

A Survey on Large Language Model based Autonomous Agents

2 code implementations22 Aug 2023 Lei Wang, Chen Ma, Xueyang Feng, Zeyu Zhang, Hao Yang, Jingsen Zhang, ZhiYuan Chen, Jiakai Tang, Xu Chen, Yankai Lin, Wayne Xin Zhao, Zhewei Wei, Ji-Rong Wen

In this paper, we present a comprehensive survey of these studies, delivering a systematic review of the field of LLM-based autonomous agents from a holistic perspective.

Language Modelling Large Language Model

Cloth2Tex: A Customized Cloth Texture Generation Pipeline for 3D Virtual Try-On

no code implementations8 Aug 2023 Daiheng Gao, Xu Chen, Xindi Zhang, Qi Wang, Ke Sun, Bang Zhang, Liefeng Bo, QiXing Huang

Since traditional warping-based texture generation methods require a significant number of control points to be manually selected for each type of garment, which can be a time-consuming and tedious process.

Texture Synthesis Virtual Try-on

Serving Graph Neural Networks With Distributed Fog Servers For Smart IoT Services

no code implementations4 Jul 2023 Liekang Zeng, Xu Chen, Peng Huang, Ke Luo, Xiaoxi Zhang, Zhi Zhou

Graph Neural Networks (GNNs) have gained growing interest in miscellaneous applications owing to their outstanding ability in extracting latent representation on graph structures.


CMLM-CSE: Based on Conditional MLM Contrastive Learning for Sentence Embeddings

no code implementations16 Jun 2023 Wei zhang, Xu Chen

Traditional comparative learning sentence embedding directly uses the encoder to extract sentence features, and then passes in the comparative loss function for learning.

Contrastive Learning Language Modelling +3

On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative Filtering

1 code implementation6 Jun 2023 Jiayan Guo, Lun Du, Xu Chen, Xiaojun Ma, Qiang Fu, Shi Han, Dongmei Zhang, Yan Zhang

Graph CF has attracted more and more attention in recent years due to its effectiveness in leveraging high-order information in the user-item bipartite graph for better recommendations.

Collaborative Filtering Recommendation Systems

User Behavior Simulation with Large Language Model based Agents

1 code implementation5 Jun 2023 Lei Wang, Jingsen Zhang, Hao Yang, ZhiYuan Chen, Jiakai Tang, Zeyu Zhang, Xu Chen, Yankai Lin, Ruihua Song, Wayne Xin Zhao, Jun Xu, Zhicheng Dou, Jun Wang, Ji-Rong Wen

Simulating high quality user behavior data has always been a fundamental problem in human-centered applications, where the major difficulty originates from the intricate mechanism of human decision process.

Language Modelling Large Language Model +2

Category-Oriented Representation Learning for Image to Multi-Modal Retrieval

no code implementations6 May 2023 Zida Cheng, Chen Ju, Shuai Xiao, Xu Chen, Zhonghua Zhai, Xiaoyi Zeng, Weilin Huang, Junchi Yan

We focus on representation learning for IMMR and analyze three key challenges for it: 1) skewed data and noisy label in real-world industrial data, 2) the information-inequality between image and text modality of documents when learning representations, 3) effective and efficient training in large-scale industrial contexts.

Cross-Modal Retrieval Image Retrieval +4

Cross-domain Augmentation Networks for Click-Through Rate Prediction

no code implementations6 May 2023 Xu Chen, Zida Cheng, Shuai Xiao, Xiaoyi Zeng, Weilin Huang

The translation network is able to compute features from two domains with heterogeneous inputs separately by designing two independent branches, and then learn meaningful cross-domain knowledge using a designed cross-supervised feature translator.

Click-Through Rate Prediction Transfer Learning +1

AG3D: Learning to Generate 3D Avatars from 2D Image Collections

no code implementations ICCV 2023 Zijian Dong, Xu Chen, Jinlong Yang, Michael J. Black, Otmar Hilliges, Andreas Geiger

The key to progress is hence to learn generative models of 3D avatars from abundant unstructured 2D image collections.

Towards Carbon-Neutral Edge Computing: Greening Edge AI by Harnessing Spot and Future Carbon Markets

no code implementations22 Apr 2023 Huirong Ma, Zhi Zhou, Xiaoxi Zhang, Xu Chen

Provisioning dynamic machine learning (ML) inference as a service for artificial intelligence (AI) applications of edge devices faces many challenges, including the trade-off among accuracy loss, carbon emission, and unknown future costs.


Dually Enhanced Propensity Score Estimation in Sequential Recommendation

1 code implementation15 Mar 2023 Chen Xu, Jun Xu, Xu Chen, Zhenghua Dong, Ji-Rong Wen

According to the graph, two complementary propensity scores are estimated from the views of item and user, respectively, based on the same set of user feedback data.

Sequential Recommendation

Vid2Avatar: 3D Avatar Reconstruction from Videos in the Wild via Self-supervised Scene Decomposition

1 code implementation CVPR 2023 Chen Guo, Tianjian Jiang, Xu Chen, Jie Song, Otmar Hilliges

Specifically, we define a temporally consistent human representation in canonical space and formulate a global optimization over the background model, the canonical human shape and texture, and per-frame human pose parameters.

3D Human Reconstruction Surface Reconstruction

Robust Mid-Pass Filtering Graph Convolutional Networks

1 code implementation16 Feb 2023 Jincheng Huang, Lun Du, Xu Chen, Qiang Fu, Shi Han, Dongmei Zhang

Theoretical analyses guarantee the robustness of signals through the mid-pass filter, and we also shed light on the properties of different frequency signals under adversarial attacks.

Adversarial Attack Node Classification

Homophily-oriented Heterogeneous Graph Rewiring

no code implementations13 Feb 2023 Jiayan Guo, Lun Du, Wendong Bi, Qiang Fu, Xiaojun Ma, Xu Chen, Shi Han, Dongmei Zhang, Yan Zhang

To this end, we propose HDHGR, a homophily-oriented deep heterogeneous graph rewiring approach that modifies the HG structure to increase the performance of HGNN.

Graph Neural Network

Fairness-aware Cross-Domain Recommendation

no code implementations1 Feb 2023 Jiakai Tang, Xu Chen, Xueyang Feng

Cross-Domain Recommendation (CDR) is an effective way to alleviate the cold-start problem.

Fairness Recommendation Systems

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.

Edge-computing Federated Learning

InstantAvatar: Learning Avatars from Monocular Video in 60 Seconds

no code implementations CVPR 2023 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 Computational Efficiency +1

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.

Computational Efficiency

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.

Graph Neural Network Miscellaneous +1

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.

Relationship Detection 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.

Benchmarking Data Augmentation +4

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).

Computational Efficiency Retrieval +1

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.

feature selection Rolling Shutter Correction +1

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

Then, it defines \emph{the MDP discrete time steps as the ranks in the initial ranking list, and the actions as the prediction of the user-item preference and the selection of the slots}.

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.

counterfactual Image Classification +2

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 Persuasiveness +1

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.


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

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

1 code implementation2 Dec 2021 Haitao Mao, Lun Du, Yujia Zheng, Qiang Fu, Zelin Li, Xu Chen, Shi Han, Dongmei Zhang

To address the non-trivial adaptation challenges in this practical scenario, we propose a model-agnostic algorithm called SOGA for domain adaptation to fully exploit the discriminative ability of the source model while preserving the consistency of structural proximity on 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

1 code implementation29 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

1 code implementation1 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 Segmentation +1

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.

counterfactual Image Classification +2

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 Generative Adversarial Network

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 counterfactual +1

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 +5

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 Decoder +3

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

1 code implementation8 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

1 code implementation22 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

However, pure correlative learning may lead to Simpson's paradox in predictions, and thus results in sacrificed recommendation performance.

Collaborative Filtering counterfactual +1

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 +4

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.


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

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 Graph Neural Network +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

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.

Attribute Graph Learning +1

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 +2

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 Node Representations against Perturbations

1 code implementation26 Aug 2020 Xu Chen, Yuangang Pan, Ivor Tsang, Ya zhang

In this paper, we study how to learn node representations against perturbations in GNN.

Contrastive Learning Node Classification +1

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 Object +1

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.


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.

counterfactual 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.

Cloud Computing 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 Generative Adversarial Network

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