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个人简介

I am a tenure-track professor with the Department of Control Science and Engineering at Tongji University. I worked as a postdoctoral researcher with Prof. Ambuj Singh on Human-AI team decision making and network science at University of California, Santa Barbara. Before that, I was a researcher with the AI Platform Department at Tencent, working on the game AI. I did my PhD at Ludwig-Maximilian University of Munich, where I was fortunately advised by Prof. Christian Böhm. I was a visiting PhD student with the iKDD research group at Helmholtz Zentrum Munich, where I worked with Prof. Claudia Plant. Awards PhD Dissertation, Data Mining Using Concepts of Independence, Unimodality and Homophily, Ludwig-Maximilian University of Munich, "Magna Cum Laude"

研究领域

数据挖掘、机器学习、网络科学和决策推理。具体包括:聚类、分类、半监督学习、图内核、图神经网络、因果推断和人机合作

近期论文

查看导师最新文章 (温馨提示:请注意重名现象,建议点开原文通过作者单位确认)

PICNN: A Pathway towards Interpretable Convolutional Neural Networks Wengang Guo, Jiayi Yang, Huilin Yin, Qijun Chen, Wei Ye AAAI Conference on Artificial Intelligence (AAAI), 2024. (CCF: A) COMBHelper: A Neural Approach to Reduce Search Space for Graph Combinatorial Problems Hao Tian, Sourav Medya, Wei Ye AAAI Conference on Artificial Intelligence (AAAI), 2024. (CCF: A) Multi-scale Wasserstein Shortest-path Graph Kernels for Graph Classification Wei Ye, Hao Tian, Qijun Chen IEEE Transactions on Artificial Intelligence (TAI), 2023. Review-Enhanced Sequential Recommendation with Self-Attention and Graph Collaborative Features Yunqi Hong, Wei Ye IEEE International Conference on Data Mining Workshops (ICDMW), 2023. Learning Deep Graph Representations via Convolutional Neural Networks (Extended abstract) Wei Ye, Omid Askarisichani, Alex Jones, Ambuj Singh IEEE International Conference on Data Engineering (ICDE), 2023. (CCF: A) Incorporating User's Preference into Attributed Graph Clustering (Extended abstract) Wei Ye, Dominik Mautz, Christian B?hm, Ambuj Singh, Claudia Plant IEEE International Conference on Data Engineering (ICDE), 2023. (CCF: A) Incorporating Heterophily into Graph Neural Networks for Graph Classification Wei Ye, Jiayi Yang, Sourav Medya, Ambuj Singh arXiv, 2022. Graph Neural Diffusion Networks for Semi-supervised Learning Wei Ye, Zexi Huang, Yunqi Hong, Ambuj Singh arXiv, 2022. Modeling Human-AI Team Decision Making Wei Ye, Francesco Bullo, Noah Friedkin, Ambuj K Singh arXiv, 2022. Deep Embedded K-Means Clustering Wengang Guo, Kaiyan Lin, Wei Ye IEEE International Conference on Data Mining Workshops (ICDMW), 2021. Learning Deep Graph Representations via Convolutional Neural Networks Wei Ye, Omid Askarisichani, Alex Jones, Ambuj Singh IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020. (CCF: A) Non-Redundant Subspace Clusterings with Nr-Kmeans and Nr-DipMeans Dominik Mautz, Wei Ye, Claudia Plant, Christian B?hm ACM Transactions on Knowledge Discovery from Data (TKDD), 2020. (CCF: B) Incorporating User's Preference into Attributed Graph Clustering Wei Ye, Dominik Mautz, Christian B?hm, Ambuj Singh, Claudia Plant IEEE Transactions on Knowledge Discovery and Data Engineering (TKDE), 2020. (CCF: A) Tree++: Truncated Tree Based Graph Kernels Wei Ye, Zhen Wang, Rachel Redberg, Ambuj Singh IEEE Transactions on Knowledge Discovery and Data Engineering (TKDE), 2019. (CCF: A) Discovering Non-Redundant K-means Clusterings in Optimal Subspaces Dominik Mautz, Wei Ye, Claudia Plant, Christian B?hm ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018. (CCF: A) Learning from Labeled and Unlabeled Vertices in Networks Wei Ye, Linfei Zhou, Dominik Mautz, Claudia Plant, Christian B?hm ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2017. (CCF: A) Towards an Optimal Subspace for KMeans Dominik Mautz, Wei Ye, Claudia Plant, Christian B?hm ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2017. (CCF: A) Attributed Graph Clustering with Unimodal Normalized Cut Wei Ye, Linfei Zhou, Xin Sun, Claudia Plant, Christian B?hm European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML-PKDD), 2017. (CCF: B) A Knowledge Discovery of Complex Data using Gaussian Mixture Models Linfei Zhou, Wei Ye, Claudia Plant, Christian B?hm International Conference on Big Data Analytics and Knowledge Discovery (DaWaK), 2017. (CCF: C) Novel Indexing Strategy and Similarity Measures for Gaussian Mixture Models Linfei Zhou, Wei Ye, Bianca Wackersreuther, Claudia Plant, Christian B?hm International Conference on Database and Expert Systems Applications (DEXA), 2017. (CCF: C) Indexing Multiple-instance Objects Linfei Zhou, Wei Ye, Zhen Wang, Claudia Plant, Christian B?hm International Conference on Database and Expert Systems Applications (DEXA), 2017. (CCF: C) Generalized Independent Subspace Clustering Wei Ye, Samuel Maurus, Nina Hubig, Claudia Plant IEEE International Conference on Data Mining (ICDM), 2016. (CCF: B) FUSE: Full Spectral Clustering Wei Ye, Sebastian Goebl, Claudia Plant, Christian B?hm ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2016. (CCF: A) IDEA: Integrative Detection of Early-stage Alzheimer’s Disease Wei Ye, Bianca Wackersreuther, Christian B?hm, Michael Ewers, Claudia Plant 5th Workshop on Data Mining for Medicine and Healthcare, SIAM International Conference on Data Mining (SDM), 2016. (CCF: B)

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