Search Results for author: Feng Xia

Found 64 papers, 11 papers with code

Millimeter Wave Radar-based Human Activity Recognition for Healthcare Monitoring Robot

no code implementations3 May 2024 Zhanzhong Gu, Xiangjian He, Gengfa Fang, Chengpei Xu, Feng Xia, Wenjing Jia

Finally, we deploy our system on a movable robot-mounted edge computing platform, achieving flexible healthcare monitoring in real-world scenarios.

Edge-computing Human Activity Recognition

FairGT: A Fairness-aware Graph Transformer

1 code implementation26 Apr 2024 Renqiang Luo, Huafei Huang, Shuo Yu, Xiuzhen Zhang, Feng Xia

The design of Graph Transformers (GTs) generally neglects considerations for fairness, resulting in biased outcomes against certain sensitive subgroups.

Fairness feature selection +1

Algorithmic Fairness: A Tolerance Perspective

no code implementations26 Apr 2024 Renqiang Luo, Tao Tang, Feng Xia, Jiaying Liu, Chengpei Xu, Leo Yu Zhang, Wei Xiang, Chengqi Zhang

Recent advancements in machine learning and deep learning have brought algorithmic fairness into sharp focus, illuminating concerns over discriminatory decision making that negatively impacts certain individuals or groups.

Decision Making Fairness

Multiple Instance Learning for Cheating Detection and Localization in Online Examinations

no code implementations9 Feb 2024 Yemeng Liu, Jing Ren, Jianshuo Xu, Xiaomei Bai, Roopdeep Kaur, Feng Xia

However, cheating behavior is rare, and most researchers do not comprehensively take into account features such as head posture, gaze angle, body posture, and background information in the task of cheating behavior detection.

Multiple Instance Learning

Learning on Multimodal Graphs: A Survey

no code implementations7 Feb 2024 Ciyuan Peng, Jiayuan He, Feng Xia

This survey paper conducts a comparative analysis of existing works in multimodal graph learning, elucidating how multimodal learning is achieved across different graph types and exploring the characteristics of prevalent learning techniques.

Graph Learning

Deep Outdated Fact Detection in Knowledge Graphs

no code implementations6 Feb 2024 Huiling Tu, Shuo Yu, Vidya Saikrishna, Feng Xia, Karin Verspoor

Knowledge graphs (KGs) have garnered significant attention for their vast potential across diverse domains.

Knowledge Graphs

Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach

1 code implementation6 Feb 2024 Xin Chen, Mingliang Hou, Tao Tang, Achhardeep Kaur, Feng Xia

With the arrival of the big data era, mobility profiling has become a viable method of utilizing enormous amounts of mobility data to create an intelligent transportation system.

Graph Learning Management

Balanced Graph Structure Information for Brain Disease Detection

1 code implementation30 Dec 2023 Falih Gozi Febrinanto, Mujie Liu, Feng Xia

In this work, we proposed Bargrain (balanced graph structure for brains), which models two graph structures: filtered correlation matrix and optimal sample graph using graph convolution networks (GCNs).

Multi-Granularity Click Confidence Learning via Self-Distillation in Recommendation

no code implementations28 Sep 2023 Chong Liu, Xiaoyang Liu, Lixin Zhang, Feng Xia, Leyu Lin

Due to the lack of supervised signals in click confidence, we first apply self-supervised learning to obtain click confidence scores via a global self-distillation method.

Recommendation Systems Self-Supervised Learning

Learning from All Sides: Diversified Positive Augmentation via Self-distillation in Recommendation

no code implementations15 Aug 2023 Chong Liu, Xiaoyang Liu, Ruobing Xie, Lixin Zhang, Feng Xia, Leyu Lin

A powerful positive item augmentation is beneficial to address the sparsity issue, while few works could jointly consider both the accuracy and diversity of these augmented training labels.

Recommendation Systems Retrieval

Coupled Attention Networks for Multivariate Time Series Anomaly Detection

no code implementations12 Jun 2023 Feng Xia, Xin Chen, Shuo Yu, Mingliang Hou, Mujie Liu, Linlin You

To address this issue, we propose a coupled attention-based neural network framework (CAN) for anomaly detection in multivariate time series data featuring dynamic variable relationships.

Anomaly Detection Decoder +5

A Survey on Fairness-aware Recommender Systems

no code implementations1 Jun 2023 Di Jin, Luzhi Wang, He Zhang, Yizhen Zheng, Weiping Ding, Feng Xia, Shirui Pan

As information filtering services, recommender systems have extremely enriched our daily life by providing personalized suggestions and facilitating people in decision-making, which makes them vital and indispensable to human society in the information era.

Decision Making Fairness +1

Graph Exploration Matters: Improving both individual-level and system-level diversity in WeChat Feed Recommender

no code implementations29 May 2023 Shuai Yang, Lixin Zhang, Feng Xia, Leyu Lin

Graph-based retrieval strategies are inevitably hijacked by heavy users and popular items, leading to the convergence of candidates for users and the lack of system-level diversity.

Recommendation Systems Retrieval

Explainable Knowledge Distillation for On-device Chest X-Ray Classification

no code implementations10 May 2023 Chakkrit Termritthikun, Ayaz Umer, Suwichaya Suwanwimolkul, Feng Xia, Ivan Lee

To overcome this problem, we propose a knowledge distillation (KD) strategy to create the compact deep learning model for the real-time multi-label CXR image classification.

Explainable artificial intelligence Explainable Artificial Intelligence (XAI) +2

Knowledge Graphs: Opportunities and Challenges

no code implementations24 Mar 2023 Ciyuan Peng, Feng Xia, Mehdi Naseriparsa, Francesco Osborne

With the explosive growth of artificial intelligence (AI) and big data, it has become vitally important to organize and represent the enormous volume of knowledge appropriately.

Knowledge Graph Embeddings

Adversarial Learning Data Augmentation for Graph Contrastive Learning in Recommendation

1 code implementation5 Feb 2023 JunJie Huang, Qi Cao, Ruobing Xie, Shaoliang Zhang, Feng Xia, HuaWei Shen, Xueqi Cheng

To reduce the influence of data sparsity, Graph Contrastive Learning (GCL) is adopted in GNN-based CF methods for enhancing performance.

Contrastive Learning Data Augmentation

Graph Learning for Anomaly Analytics: Algorithms, Applications, and Challenges

no code implementations11 Dec 2022 Jing Ren, Feng Xia, Azadeh Noori Hoshyar, Charu C. Aggarwal

Anomaly analytics is a popular and vital task in various research contexts, which has been studied for several decades.

Graph Attention Graph Classification +3

Fully Automated Deep Learning-enabled Detection for Hepatic Steatosis on Computed Tomography: A Multicenter International Validation Study

no code implementations27 Oct 2022 Zhongyi Zhang, Guixia Li, Ziqiang Wang, Feng Xia, Ning Zhao, Huibin Nie, Zezhong Ye, Joshua Lin, Yiyi Hui, Xiangchun Liu

To automate the process, we validated an existing artificial intelligence (AI) system for 3D liver segmentation and used it to purpose a novel method: AI-ROI, which could automatically select the ROI for attenuation measurements.

Computed Tomography (CT) Liver Segmentation +1

Pruning Pre-trained Language Models Without Fine-Tuning

1 code implementation12 Oct 2022 Ting Jiang, Deqing Wang, Fuzhen Zhuang, Ruobing Xie, Feng Xia

These methods, such as movement pruning, use first-order information to prune PLMs while fine-tuning the remaining weights.

Reweighting Clicks with Dwell Time in Recommendation

no code implementations19 Sep 2022 Ruobing Xie, Lin Ma, Shaoliang Zhang, Feng Xia, Leyu Lin

Precisely, we first define a new behavior named valid read, which helps to select high-quality click instances for different users and items via dwell time.


CHIEF: Clustering with Higher-order Motifs in Big Networks

no code implementations6 Apr 2022 Feng Xia, Shuo Yu, Chengfei Liu, Ivan Lee

In the first procedure, we propose to lower the network scale by optimizing the network structure with maximal k-edge-connected subgraphs.


Graph Augmentation Learning

1 code implementation17 Mar 2022 Shuo Yu, Huafei Huang, Minh N. Dao, Feng Xia

To better show the outperformance of GAL, we experimentally validate the effectiveness and adaptability of different GAL strategies in different downstream tasks.

Graph Learning

Deep Graph Learning for Anomalous Citation Detection

no code implementations23 Feb 2022 Jiaying Liu, Feng Xia, Xu Feng, Jing Ren, Huan Liu

To address this open issue, we propose a novel deep graph learning model, namely GLAD (Graph Learning for Anomaly Detection), to identify anomalies in citation networks.

Anomaly Detection Graph Learning +1

Web of Scholars: A Scholar Knowledge Graph

no code implementations23 Feb 2022 Jiaying Liu, Jing Ren, Wenqing Zheng, Lianhua Chi, Ivan Lee, Feng Xia

In this work, we demonstrate a novel system, namely Web of Scholars, which integrates state-of-the-art mining techniques to search, mine, and visualize complex networks behind scholars in the field of Computer Science.

Physics-Informed Graph Learning

no code implementations22 Feb 2022 Ciyuan Peng, Feng Xia, Vidya Saikrishna, Huan Liu

The graph learning models suffer from the inability to efficiently learn graph information.

Graph Learning

Graph Lifelong Learning: A Survey

no code implementations22 Feb 2022 Falih Gozi Febrinanto, Feng Xia, Kristen Moore, Chandra Thapa, Charu Aggarwal

Lifelong learning methods that enable continuous learning in regular domains like images and text cannot be directly applied to continuously evolving graph data, due to its irregular structure.

Graph Learning Recommendation Systems

Surf or sleep? Understanding the influence of bedtime patterns on campus

no code implementations18 Feb 2022 Teng Guo, Linhong Li, Dongyu Zhang, Feng Xia

In this paper, we develop a general data-driven method for identifying students' sleep patterns according to their Internet access pattern stored in the education management system and explore its influence from various aspects.


The Gene of Scientific Success

no code implementations17 Feb 2022 Xiangjie Kong, Jun Zhang, Da Zhang, Yi Bu, Ying Ding, Feng Xia

Under this consideration, our paper presents and analyzes the causal factors that are crucial for scholars' academic success.

Exploring Human Mobility for Multi-Pattern Passenger Prediction: A Graph Learning Framework

no code implementations17 Feb 2022 Xiangjie Kong, Kailai Wang, Mingliang Hou, Feng Xia, Gour Karmakar, JianXin Li

To reduce this research gap and learn human mobility knowledge from this fixed travel behaviors, we propose a multi-pattern passenger flow prediction framework, MPGCN, based on Graph Convolutional Network (GCN).

Deep Clustering Graph Learning

Heterogeneous Graph Learning for Explainable Recommendation over Academic Networks

no code implementations16 Feb 2022 Xiangtai Chen, Tao Tang, Jing Ren, Ivan Lee, Honglong Chen, Feng Xia

We devise an unsupervised learning model called HAI (Heterogeneous graph Attention InfoMax) which aggregates attention mechanism and mutual information for institution recommendation.

Explainable Recommendation Graph Attention +1

CenGCN: Centralized Convolutional Networks with Vertex Imbalance for Scale-Free Graphs

no code implementations16 Feb 2022 Feng Xia, Lei Wang, Tao Tang, Xin Chen, Xiangjie Kong, Giles Oatley, Irwin King

In each non-output layer of the GCN, this framework uses a hub attention mechanism to assign new weights to connected non-hub vertices based on their common information with hub vertices.

Link Prediction

Edge Data Based Trailer Inception Probabilistic Matrix Factorization for Context-Aware Movie Recommendation

no code implementations16 Feb 2022 Honglong Chen, Zhe Li, Zhu Wang, Zhichen Ni, Junjian Li, Ge Xu, Abdul Aziz, Feng Xia

As an effective way to alleviate information overload, recommender system can improve the quality of various services by adding application data generated by users on edge devices, such as visual and textual information, on the basis of sparse rating data.

Movie Recommendation Recommendation Systems

VRConvMF: Visual Recurrent Convolutional Matrix Factorization for Movie Recommendation

no code implementations16 Feb 2022 Zhu Wang, Honglong Chen, Zhe Li, Kai Lin, Nan Jiang, Feng Xia

Fortunately, context-aware recommender systems can alleviate the sparsity problem by making use of some auxiliary information, such as the information of both the users and items.

Descriptive Movie Recommendation +1

Curriculum Disentangled Recommendation with Noisy Multi-feedback

1 code implementation NeurIPS 2021 Hong Chen, Yudong Chen, Xin Wang, Ruobing Xie, Rui Wang, Feng Xia, Wenwu Zhu

However, learning such disentangled representations from multi-feedback data is challenging because i) multi-feedback is complex: there exist complex relations among different types of feedback (e. g., click, unclick, and dislike, etc) as well as various user intentions, and ii) multi-feedback is noisy: there exists noisy (useless) information both in features and labels, which may deteriorate the recommendation performance.

Denoising Representation Learning

Deep Video Anomaly Detection: Opportunities and Challenges

no code implementations11 Oct 2021 Jing Ren, Feng Xia, Yemeng Liu, Ivan Lee

Moreover, we summarise the characteristics and technical problems in current deep learning methods for video anomaly detection.

Anomaly Detection Video Anomaly Detection

Heterogeneous network-based drug repurposing for COVID-19

1 code implementation20 Jul 2021 Shuting Jin, Xiangxiang Zeng, Wei Huang, Feng Xia, Changzhi Jiang, Xiangrong Liu, Shaoliang Peng

The Corona Virus Disease 2019 (COVID-19) belongs to human coronaviruses (HCoVs), which spreads rapidly around the world.

Solving ESL Sentence Completion Questions via Pre-trained Neural Language Models

1 code implementation15 Jul 2021 Qiongqiong Liu, Tianqiao Liu, Jiafu Zhao, Qiang Fang, Wenbiao Ding, Zhongqin Wu, Feng Xia, Jiliang Tang, Zitao Liu

Sentence completion (SC) questions present a sentence with one or more blanks that need to be filled in, three to five possible words or phrases as options.

Sentence Sentence Completion

Multiple-Input Multiple-Output Fusion Network For Generalized Zero-Shot Learning

no code implementations IEEE 2021 Fangming Zhong∗, Guangze Wang, Zhikui Chen, Xu Yuan, Feng Xia

Generalized zero-shot learning (GZSL) has attracted consid- erable attention recently, which trains models with data from seen classes and tests on data from both seen and unseen classes.

Generalized Zero-Shot Learning

Long Short-Term Temporal Meta-learning in Online Recommendation

no code implementations8 May 2021 Ruobing Xie, Yalong Wang, Rui Wang, Yuanfu Lu, Yuanhang Zou, Feng Xia, Leyu Lin

An effective online recommendation system should jointly capture users' long-term and short-term preferences in both users' internal behaviors (from the target recommendation task) and external behaviors (from other tasks).


Graph Learning: A Survey

no code implementations3 May 2021 Feng Xia, Ke Sun, Shuo Yu, Abdul Aziz, Liangtian Wan, Shirui Pan, Huan Liu

In this survey, we present a comprehensive overview on the state-of-the-art of graph learning.

BIG-bench Machine Learning Combinatorial Optimization +3

Network Representation Learning: From Traditional Feature Learning to Deep Learning

no code implementations7 Mar 2021 Ke Sun, Lei Wang, Bo Xu, Wenhong Zhao, Shyh Wei Teng, Feng Xia

Network representation learning (NRL) is an effective graph analytics technique and promotes users to deeply understand the hidden characteristics of graph data.

Recommendation Systems Representation Learning

Graph Force Learning

no code implementations7 Mar 2021 Ke Sun, Jiaying Liu, Shuo Yu, Bo Xu, Feng Xia

Features representation leverages the great power in network analysis tasks.

Graph Learning

Matching Algorithms: Fundamentals, Applications and Challenges

no code implementations5 Mar 2021 Jing Ren, Feng Xia, Xiangtai Chen, Jiaying Liu, Mingliang Hou, Ahsan Shehzad, Nargiz Sultanova, Xiangjie Kong

Based on the preference list access, matching problems are divided into two categories, i. e., explicit matching and implicit matching.

Information Retrieval Recommendation Systems Social and Information Networks

OFFER: A Motif Dimensional Framework for Network Representation Learning

no code implementations27 Aug 2020 Shuo Yu, Feng Xia, Jin Xu, Zhikui Chen, Ivan Lee

In order to assess the efficiency of the proposed framework, four popular network representation algorithms are modified and examined.

Clustering Graph Learning +2

Understanding the Advisor-advisee Relationship via Scholarly Data Analysis

no code implementations20 Aug 2020 Jiaying Liu, Tao Tang, Xiangjie Kong, Amr Tolba, Zafer AL-Makhadmeh, Feng Xia

Advisor-advisee relationship is important in academic networks due to its universality and necessity.

Shifu2: A Network Representation Learning Based Model for Advisor-advisee Relationship Mining

no code implementations17 Aug 2020 Jiaying Liu, Feng Xia, Lei Wang, Bo Xu, Xiangjie Kong, Hanghang Tong, Irwin King

The advisor-advisee relationship represents direct knowledge heritage, and such relationship may not be readily available from academic libraries and search engines.

Representation Learning

Scientific Paper Recommendation: A Survey

no code implementations10 Aug 2020 Xiaomei Bai, Mengyang Wang, Ivan Lee, Zhuo Yang, Xiangjie Kong, Feng Xia

The problem of recommending similar scientific articles in scientific community is called scientific paper recommendation.

Collaborative Filtering Recommendation Systems

The Role of Positive and Negative Citations in Scientific Evaluation

no code implementations10 Aug 2020 Xiaomei Bai, Ivan Lee, Zhaolong Ning, Amr Tolba, Feng Xia

Quantifying the impact of scientific papers objectively is crucial for research output assessment, which subsequently affects institution and country rankings, research funding allocations, academic recruitment and national/international scientific priorities.

Socially-Aware Conference Participant Recommendation with Personality Traits

no code implementations9 Aug 2020 Feng Xia, Nana Yaw Asabere, Haifeng Liu, Zhen Chen, Wei Wang

As a result of the importance of academic collaboration at smart conferences, various researchers have utilized recommender systems to generate effective recommendations for participants.

Recommendation Systems

Big Networks: A Survey

no code implementations9 Aug 2020 Hayat Dino Bedru, Shuo Yu, Xinru Xiao, Da Zhang, Liangtian Wan, He guo, Feng Xia

This paper proposes a guideline framework that gives an insight into the major topics in the area of network science from the viewpoint of a big network.

Community Detection Link Prediction +1

Random Walks: A Review of Algorithms and Applications

no code implementations9 Aug 2020 Feng Xia, Jiaying Liu, Hansong Nie, Yonghao Fu, Liangtian Wan, Xiangjie Kong

In this paper, we aim to provide a comprehensive review of classical random walks and quantum walks.

Link Prediction Network Embedding

MODEL: Motif-based Deep Feature Learning for Link Prediction

no code implementations9 Aug 2020 Lei Wang, Jing Ren, Bo Xu, Jian-Xin Li, Wei Luo, Feng Xia

Link prediction plays an important role in network analysis and applications.

Link Prediction

Multivariate Relations Aggregation Learning in Social Networks

no code implementations9 Aug 2020 Jin Xu, Shuo Yu, Ke Sun, Jing Ren, Ivan Lee, Shirui Pan, Feng Xia

Therefore, in graph learning tasks of social networks, the identification and utilization of multivariate relationship information are more important.

Attribute Graph Learning +1

DINE: A Framework for Deep Incomplete Network Embedding

no code implementations9 Aug 2020 Ke Hou, Jiaying Liu, Yin Peng, Bo Xu, Ivan Lee, Feng Xia

Empirically, we evaluate DINE over three networks on multi-label classification and link prediction tasks.

General Classification Link Prediction +3

Graduate Employment Prediction with Bias

no code implementations27 Dec 2019 Teng Guo, Feng Xia, Shihao Zhen, Xiaomei Bai, Dongyu Zhang, Zitao Liu, Jiliang Tang

The failure of landing a job for college students could cause serious social consequences such as drunkenness and suicide.

Generative Adversarial Network

Telling the Whole Story: A Manually Annotated Chinese Dataset for the Analysis of Humor in Jokes

no code implementations IJCNLP 2019 Dongyu Zhang, Heting Zhang, Xikai Liu, Hongfei Lin, Feng Xia

To the best of our knowledge, we are the first to approach humor annotation for exploring the underlying mechanism of the use of humor, which may contribute to a significantly deeper analysis of humor.

Iterative Nearest Neighborhood Oversampling in Semisupervised Learning from Imbalanced Data

no code implementations24 Dec 2013 Fengqi Li, Chuang Yu, Nanhai Yang, Feng Xia, Guangming Li, Fatemeh Kaveh-Yazdy

Transductive graph-based semi-supervised learning methods usually build an undirected graph utilizing both labeled and unlabeled samples as vertices.

General Classification imbalanced classification

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