Balanced Distribution Adaptation for Transfer Learning. - Jindong Wang 001; Yiqiang Chen 001; Shuji Hao; Wenjie Feng 001; Zhiqi Shen 001 (ICDM, 2017)

EagleMine: Vision-Guided Mining in Large Graphs. - Wenjie Feng 001; Shenghua Liu; Christos Faloutsos; Bryan Hooi; Huawei Shen; Xueqi Cheng (CoRR, 2017)

Visual Domain Adaptation with Manifold Embedded Distribution Alignment. - Jindong Wang 001; Wenjie Feng 001; Yiqiang Chen 001; Han Yu 001; Meiyu Huang; Philip S. Yu (ACM Multimedia, 2018)

Beyond Outliers and on to Micro-clusters: Vision-Guided Anomaly Detection. - Wenjie Feng 001; Shenghua Liu; Christos Faloutsos; Bryan Hooi; Huawei Shen; Xueqi Cheng (PAKDD (1), 2019)

EigenPulse: Detecting Surges in Large Streaming Graphs with Row Augmentation. - Jiabao Zhang; Shenghua Liu; Wenjian Yu; Wenjie Feng 001; Xueqi Cheng (PAKDD (2), 2019)

CatchCore: Catching Hierarchical Dense Subtensor. - Wenjie Feng 001; Shenghua Liu; Xueqi Cheng (ECML/PKDD (1), 2019)

SpecGreedy: Unified Dense Subgraph Detection. - Wenjie Feng 001; Shenghua Liu; Danai Koutra; Huawei Shen; Xueqi Cheng (ECML/PKDD (1), 2020)

Learning to Match Distributions for Domain Adaptation. - Chaohui Yu; Jindong Wang 001; Chang Liu 030; Tao Qin 001; Renjun Xu; Wenjie Feng 001; Yiqiang Chen 001; Tie-Yan Liu (CoRR, 2020)

Transfer Learning with Dynamic Distribution Adaptation. - Jindong Wang 001; Yiqiang Chen 001; Wenjie Feng 001; Han Yu 001; Meiyu Huang; Qiang Yang 001 (ACM Trans. Intell. Syst. Technol., 2020)

AdaRNN: Adaptive Learning and Forecasting of Time Series. - Yuntao Du 001; Jindong Wang 001; Wenjie Feng 001; Sinno Jialin Pan; Tao Qin 001; Renjun Xu; Chongjun Wang (CIKM, 2021)

Learning Invariant Representations across Domains and Tasks. - Jindong Wang 001; Wenjie Feng 001; Chang Liu 030; Chaohui Yu; Mingxuan Du; Renjun Xu; Tao Qin 001; Tie-Yan Liu (CoRR, 2021)

EagleMine: Vision-guided Micro-clusters recognition and collective anomaly detection. - Wenjie Feng 001; Shenghua Liu; Christos Faloutsos; Bryan Hooi; Huawei Shen; Xueqi Cheng (Future Gener. Comput. Syst., 2021)

MonLAD: Money Laundering Agents Detection in Transaction Streams. - Xiaobing Sun; Wenjie Feng 001; Shenghua Liu; Yuyang Xie; Siddharth Bhatia 001; Bryan Hooi; Wenhan Wang; Xueqi Cheng (WSDM, 2022)

Birds of a Feather Trust Together: Knowing When to Trust a Classifier via Adaptive Neighborhood Aggregation. - Miao Xiong; Shen Li 004; Wenjie Feng 001; Ailin Deng; Jihai Zhang 002; Bryan Hooi (Trans. Mach. Learn. Res., 2022)

Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering. - Mingqi Yang; Wenjie Feng 001; Yanming Shen; Bryan Hooi (ICML, 2023)

EasySpider: A No-Code Visual System for Crawling the Web. - Naibo Wang; Wenjie Feng 001; Jianwei Yin; See-Kiong Ng (WWW (Companion Volume), 2023)

Data-Free Diversity-Based Ensemble Selection For One-Shot Federated Learning in Machine Learning Model Market. - Naibo Wang; Wenjie Feng 001; Fusheng Liu; Moming Duan; See-Kiong Ng (CoRR, 2023)

Fast Searching The Densest Subgraph And Decomposition With Local Optimality. - Yugao Zhu; Shenghua Liu; Wenjie Feng 001; Xueqi Cheng (CoRR, 2023)

Data-Free Diversity-Based Ensemble Selection for One-Shot Federated Learning. - Naibo Wang; Wenjie Feng 001; Yuchen Deng; Moming Duan; Fusheng Liu; See-Kiong Ng (Trans. Mach. Learn. Res., 2023)

Hierarchical Dense Pattern Detection in Tensors. - Wenjie Feng 001; Shenghua Liu; Xueqi Cheng (ACM Trans. Knowl. Discov. Data, 2023)

One-Shot Sequential Federated Learning for Non-IID Data by Enhancing Local Model Diversity. - Naibo Wang; Yuchen Deng; Wenjie Feng 001; Shichen Fan; Jianwei Yin; See-Kiong Ng (ACM Multimedia, 2024)

SemRoDe: Macro Adversarial Training to Learn Representations that are Robust to Word-Level Attacks. - Brian Formento; Wenjie Feng 001; Chuan-Sheng Foo; Anh Tuan Luu; See-Kiong Ng (NAACL-HLT, 2024)

ID3: Identity-Preserving-yet-Diversified Diffusion Models for Synthetic Face Recognition. - Jianqing Xu; Shen Li 004; Jiaying Wu; Miao Xiong; Ailin Deng; Jiazhen Ji; Yuge Huang; Guodong Mu; Wenjie Feng 001; Shouhong Ding; Bryan Hooi (NeurIPS, 2024)

Graph Descriptive Order Improves Reasoning with Large Language Model. - Yuyao Ge; Shenghua Liu; Wenjie Feng 001; Lingrui Mei; Lizhe Chen; Xueqi Cheng (CoRR, 2024)

Data-Free Federated Class Incremental Learning with Diffusion-Based Generative Memory. - Naibo Wang; Yuchen Deng; Wenjie Feng 001; Jianwei Yin; See-Kiong Ng (CoRR, 2024)

ID3: Identity-Preserving-yet-Diversified Diffusion Models for Synthetic Face Recognition. - Shen Li 004; Jianqing Xu; Jiaying Wu; Miao Xiong; Ailin Deng; Jiazhen Ji; Yuge Huang; Wenjie Feng 001; Shouhong Ding; Bryan Hooi (CoRR, 2024)

Unified Dense Subgraph Detection: Fast Spectral Theory Based Algorithms. - Wenjie Feng 001; Shenghua Liu; Danai Koutra; Xueqi Cheng (IEEE Trans. Knowl. Data Eng., 2024)

Interrelated Dense Pattern Detection in Multilayer Networks. - Wenjie Feng 001; Li Wang 142; Bryan Hooi; See-Kiong Ng; Shenghua Liu (IEEE Trans. Knowl. Data Eng., 2024)

Can Graph Descriptive Order Affect Solving Graph Problems with LLMs? - Yuyao Ge; Shenghua Liu; Baolong Bi; Yiwei Wang 001; Lingrui Mei; Wenjie Feng 001; Lizhe Chen; Xueqi Cheng (ACL (1), 2025)

Interrelated Dense Pattern Detection in Multilayer Networks (Extended Abstract). - Wenjie Feng 001; Li Wang 142; Bryan Hooi; See-Kiong Ng; Shenhua Liu (ICDE, 2025)

Rethinking Machine Unlearning in Image Generation Models. - Renyang Liu; Wenjie Feng 001; Tianwei Zhang; Wei Zhou; Xueqi Cheng; See-Kiong Ng (CoRR, 2025)