个人简介
青年副研究员。2020年获得纽约州立大学奥尔巴尼分校博士学位，之后在石溪大学从事博士后研究工作（2020-2021）。其主要研究成果已发表于ICDM，SDM，KDD，IJCAI，ICML，TKDE等国际会议和期刊上。
Education
2020 Ph.D. in Computer Science, University at Albany, Albany, NY
Thesis title: Optimization methods for learning graph-structured sparse models
Committee: Petko Bogdanov, Feng Chen, Siwei Lyu, Won Namgoong, and Yiming Ying
Committee chair: Won Namgoong
Thesis advisor: Feng Chen
Date of defense: 12/16/2019
2020 M.A. in Mathematics, University at Albany, Albany, NY
2014 MSc. in Computer Science. Beihang University, Beijing, China
2011 B.S. in Computer Science, Anhui University, Hefei, China
Honors and Awards
Dean’s Scholarship Award, 2019, Department of Mathematics, University at Albany, SUNY.
Student Travel Award, KDD, 2019, Anchorage, Alaska, USA.
Student Travel Award, ICML, 2019, Long Beach, California, USA.
近期论文
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Zhou, Baojian, and Yifan Sun. Approximate Frank-Wolfe Algorithms over Graph-structured Support Sets, In International Conference on Machine Learning (ICML), pp. 27303-27337. PMLR, ArXiv, 2022, Code.
Guo, Xingzhi, Baojian Zhou, and Steven Skiena. Subset Node Anomaly Tracking over Large Dynamic Graphs. arXiv preprint arXiv:2205.09786, ArXiv, 2022.
Guo, Xingzhi, Baojian Zhou, and Steven Skiena. Subset Node Representation Learning over Large Dynamic Graphs https:dl.acm.orgdoi10.1145/3447548.3467393 Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD, 2021. Code
Xingzhi Guo and Baojian Zhou and Haochen Chen and Sergiy Verstyuk and Steven Skiena. Why do embedding spaces look as they do?, 2021
Baojian Zhou, Yiming Ying, Steven Skiena Online AUC Optimization for Sparse High-Dimensional Datasets for AUC Maximization, ICDM, 2020, Code, ArXiv
Zhenhuan Yang, Baojian Zhou, Yunwen Lei, Yiming Ying, Stochastic Hard Thresholding Algorithms for AUC Maximization, ICDM, 2020, Code, ArXiv
Rongrong Tao, Baojian Zhou, Feng Chen, David Mares, Patrick Butler, Naren Ramakrishnan, Ryan Kennedy Detecting Media Self-Censorship without Explicit Training Data, SDM, 2020
Baojian Zhou, Feng Chen, Yiming Ying, Dual Averaging Method for Online Graph-structured Sparsity, The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD, 2019,Webpage, ArXiv
Baojian Zhou, Feng Chen, Yiming Ying, Stochastic Iterative Hard Thresholding for Graph-structured Sparsity Optimization, International Conference on Machine Learning, ICML, 2019, Webpage, Paper, ArXiv, Slides, Poster
Boyang Hu*, Baojian Zhou*, Qiben Yan, Alim Adil, Feng Chen, and Huacheng Zeng, Naifeng Liu, David Mares, Patrick Butler, Naren Ramakrishnan. PSCluster: Differentially Private Spatial Cluster Detection for Mobile Crowdsourcing Applications, 2018. In Proceedings of the IEEE International Conference on Computer Communications and Network Security (CNS), 2018.
Nannan Wu, Feng Chen, Jianxin Li, Jinpeng Huai, Baojian Zhou, Bo Li, Naren Ramakrishnan, A Nonparametric Approach to Uncovering Connected Anomalies by Tree Shaped Priors, 2018. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2018.
Feng Chen, Baojian Zhou*, Adil Alim*, and Liang Zhao. A Generic Framework for Interesting Subspace Cluster Detection in Multi-attributed Networks, In Proceedings of the IEEE International Conference on Data Mining (ICDM), pages 41-50, 2017 arXiv, Code.
Rongrong Tao, Baojian Zhou, Feng Chen, Naifeng Liu, David Mares, Patrick Butler, Naren Ramakrishnan. Can Self-Censorship in News Media be Detected Algorithmically? A Case Study in Latin America, arXiv
Baojian Zhou, and Feng, Chen. Graph-Structured Sparse Optimization for Connected Subgraph Detection, IEEE International Conference on Data Mining, ICDM,Code, Paper, Regular paper; acceptance rate: 8.4%.
Feng Chen, and Baojian Zhou. A Generalized Matching Pursuit Approach for Graph-Structured Sparsity. Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI, 2016.Code, arXiv.
Yu Liu, Baojian Zhou, Feng Chen, and David W. Cheung. Graph Topic Scan Statistic for Spatial Event Detection. In Proceedings of the 25th ACM International Conference on Information and Knowledge Management, CIKM, 2016, Paper, Long paper, acceptance rate: 17.6%.
Wu, Nannan, Feng Chen, Jianxin Li, Baojian Zhou, and Naren Ramakrishnan. Efficient Nonparametric Subgraph Detection using Tree Shaped Priors, In Thirtieth AAAI Conference on Artificial Intelligence, AAAI, 2016, Paper.
Jieyu Zhao, Jianxin Li, Baojian Zhou, Feng Chen, Paul Tomchik, Wuyang Ju. Parallel Algorithms for Anomalous Subgraph Detection, In Journal of Concurrency and Computation: Practice and Experience, 2016.
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