Journal

[J] Interrelated Dense Pattern Detection in Multilayer Networks
Wenjie Feng, Li Wang, Bryan Hooi, See-Kiong Ng, and Shenghua Liu.
IEEE Transactions on Knowledge and Data Engineering (TKDE)
[ paper | code and datasets | bib]

[J] Unified Dense Subgraph Detection: Fast Spectral Theory-based Algorithms
Wenjie Feng, Shenghua Liu, Danai Koutra, Xueqi Cheng.
IEEE Transactions on Knowledge and Data Engineering (TKDE).
[ paper | code and datasets | bib]

[J] Data-Free Diversity-Based Ensemble Selection For One-Shot Federated Learning
Naibo Wang, Wenjie Feng#, Yuchen Deng, Moming Duan, Fusheng Liu, See-Kiong Ng.
Transactions on Machine Learning Research (TMLR).
[ paper | code and datasets | bib]

[J] Hierarchical Dense Pattern Detection in Tensors
Wenjie Feng, Shenghua Liu, Xueqi Cheng.
Transactions on Knowledge Discovery (TKDD).
[paper | code and datasets | bib]

[J] Birds of a Feather Trust Together: Knowing When to Trust a Classifier via Adaptive Neighborhood Aggregation
Miao Xiong, Shen Li, Wenjie Feng, Ailin Deng, Jihai Zhang, Bryan Hooi.
Transactions on Machine Learning Research (TMLR).
[paper | code and datasets | bib]

[J] EagleMine: Vision-guided Micro-clusters recognition and collective anomaly detection
Wenjie Feng, Shenghua Liu, Christos Faloutsos, Bryan Hooi, Huawei Shen, and Xueqi Cheng.
Future Generation Computer Systems (FGCS).
[paper | code and datasets | bib]

[J] Transfer Learning with Dynamic Distribution Adaptation
Jindong Wang, Yiqiang Chen, Wenjie Feng, Han Yu, Meiyu Huang, Qiang Yang.
ACM Transactions on Intelligent Systems and Technology (TIST).
[paper | code and datasets | bib]

Conference

[C] Interrelated Dense Pattern Detection in Multilayer Networks (Extended Abstract)
Wenjie Feng, Li Wang, Bryan Hooi, See-Kiong Ng, and Shenghua Liu.
IEEE International Conference on Data Engineering. ICDE 2025
[ paper | code | bib]

[C] Densest Subgraph Fast-searching and Decomposition with Local Optimality (Under submission)
Yugao Zhu, Shenghua Liu, Wenjie Feng#, Xueqi Cheng.
[ paper | pre-print | code and datasets | bib]

[C] ID3: Identity-Preserving-yet-Diversified Diffusion Models for Synthetic Face Recognition.
Jianqing Xu, Shen Li, Jiaying Wu, Miao Xiong, Ailin Deng, Jiazhen Ji, Yuge Huang, Guodong Mu, Wenjie Feng, Shouhong Ding, Bryan Hooi
Thirty-eighth Annual Conference on Neural Information Processing Systems. NeurIPS 2024
[ paper | ArXiv | code and datasets | bib]

[C] One-Shot Sequential Federated Learning for Non-IID Data by Enhancing Local Model Diversity.
Naibo Wang, Yuchen Deng, Wenjie Feng#, Shichen Fan, Jianwei Yin, See-Kiong Ng.
The 32nd ACM International Conference on Multimedia. ACM Multimedia . ACM MM 2024.
[ paper | ArXiv | code and datasets | bib]

[C] SemRode: Macro Adversarial Training to Learn Representations That are Robust to Word-Level Attacks
Brian Formento, Wenjie Feng#, Chuan-Sheng Foo, Anh Tuan Luu, See-Kiong Ng.
2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics. (NAACL), 2024
[ paper | ArXiv | code and datasets | bib]

[C] Towards Better Graph Representation Learning with Parameterized Decomposition \& Filtering
Mingqi Yang, Wenjie Feng, Yanming Shen, Bryan Hooi.
Proceedings of the 40th International Conference on Machine Learning. ICML 2023
[ paper |code and datasets | bib]

[D&P] EasySpider: A No-Code Visual System for Crawling the Web
Naibo Wang, Wenjie Feng, Jianwei Yin, See-Kiong Ng.
Proceedings of the ACM Web Conference. The WebConf Demo & Poster 2023
[paper | code | video | bib]

[C] MonLAD: Money Laundering Agents Detection in Transaction Streams
Xiaobing Sun*, Wenjie Feng*, Shenghua Liu, Yuyang Xie, Bryan Hooi, Wenhan Wang, and Xueqi Cheng.
The 15th International Conference on Web Search and Data Mining. WSDM 2022.
[paper | slides | video | code and datasets | bib]

[C] AdaRNN: Adaptive Learning and Forecasting of Time Series
Yuntao Du, Jindong Wang, Wenjie Feng#, Sinno Pan, Tao Qin, Renjun Xu, Chongjun Wang.
The 30th ACM International Conference on Information and Knowledge Management . CIKM 2021.
[paper | video | code and datasets | bib]

[C] SpecGreedy: Unified Dense Subgraph Detection
Wenjie Feng, Shenghua Liu, Danai Koutra, Huawei Shen, and Xueqi Cheng.
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML-PKDD 2020. (Best DM Student Paper Award).
[paper | slides | appendix | video | code and datasets | bib]

[C] CachCore: Catching Hierarchical Dense Subtensor
Wenjie Feng, Shenghua Liu, Xueqi Cheng.
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (Long Talk). ECML-PKDD 2019.
[paper | slides | appendix | poster | code and datasets | bib]

[C] Beyond outliers and on to micro-clusters: Vision-guided anomaly detection
Wenjie Feng, Shenghua Liu, Christos Faloutsos, Bryan Hooi, Huawei Shen, and Xueqi Cheng.
The 23rd Pacific-Asia Conference in Knowledge Discovery and Data Mining (Long Talk). PAKDD 2019.
[paper | slides | appendix | poster | code and datasets | bib]

[C] EigenPulse: Detecting Surges in Large Streaming Graphs with Row Augmentation
Jiabao Zhang, Shenghua Liu, Wenjian Yu, Wenjie Feng, Xueqi Cheng.
The 23rd Pacific-Asia Conference in Knowledge Discovery and Data Mining (Long Talk). PAKDD 2019.
[paper | slides | appendix | poster | code and datasets | bib]

[C] Visual Domain Adaptation with Manifold Embedded Distribution Alignment
Jindong Wang*, Wenjie Feng*, Yiqiang, Chen, Han Yu, Philip S Yu.
The 26th ACM International Conference on Multimedia. ACM Multimedia (Long Talk). ACM MM 2018.
[paper | slides | code and datasets | bib]

[CW] EagleMine: Vision-Guided Mining in Large Graphs
Wenjie Feng, Shenghua Liu, Christos Faloutsos, Bryan Hooi, Huawei Shen, and Xueqi Cheng.
KDD Outlier Detection De-constructed (ODD) Workshop (Long Talk). KDD ODDv5.0 2018.
[paper | slides | appendix | poster | code and datasets | bib]

[C] Balanced Distribution Adaptation for Transfer Learning
Jindong Wang, Yiqiang Chen, Shuji Hao, Wenjie Feng, Zhiqi Shen.
IEEE International Conference on Data Mining (Short) . ICDM 2017.
[paper | slides | code and datasets | bib]

Technical reports

Learning Invariant Representations across Domains and Tasks.
Jindong Wang, Wenjie Feng, Chang Liu, Chaohui Yu, Mingxuan Du, Renjun Xu, Tao Qin, Tie-Yan Liu.
arXiv Pre-print CoRR .

Learning to Match Distributions for Domain Adaptation.
Chaohui Yu, Jindong Wang, Chang Liu, Tao Qin, Renjun Xu, Wenjie Feng, Yiqiang Chen, Tie-Yan Liu.
arXiv Pre-print CoRR .

Dissertation (Chinese)

Feng Wenjie . Collective Anomaly Pattern Mining in Large-Scale Graph Data (In Chinese)

[* denotes equal contribution, # denotes corresponding author]