张广怡 Zhang Guangyi

助理教授

深圳技术大学 大数据与互联网学院

Data Mining , Algorithms

简介  ABOUT

动态   NEWS

学术   ACADEMIC

My research interests broadly lie in algorithms with provable approximation guarantees for data mining. 

Selected topics include submodular optimization, explainable rule-based systems, active learning, diversity maximization, and graph mining.

Don’t hesitate to send me an e-mail if you want to work with me or discuss my works.

Email: guangyi.z AT outlook.com

Education

Ph.D. in Computer Science, KTH Royal Institute of Technology, Sweden, 2023

- I am fortunate to be supervised by Prof. Aristides Gionis and my thesis can be found here

M.S. in Machine Learning and Data Mining (Macadamia), Aalto University, Finland, 2019

B.Eng. in Software Engineering, South China University of Technology (SCUT, 华南理工大学), China, 2015

Awards

Best paper award at the 2023 SIAM International Conference on Data Mining (SDM 2023)

Aalto University Scholarship (category A with 100% waiver), 2017-2019

腾讯奖学金 Tencent Innovation Scholarship (2/293), 2014

国家奖学金 National Scholarship of China (5/293), 2013

Teaching

SZTU

- Introduction to C Programming, teacher

KTH

- Advanced Algorithms (DD2440), assistant x3

- Introduction to the Philosophy of Science and Research Methodology for Computer Scientists (DA2210), assistant

- Algorithms and Complexity (DD2352), assistant x2

- Program System Construction Using C++ (DD1388), assistant x3

Services

PC Member:

KDD 2023, 2024

WSDM 2023, 2024

Subreviewer: WebConf 2022, ICML 2022, ICDM 2022, CIKM 2023

Publications

While I love all my papers, papers 3,5,7 are the closest to my heart.

See also Google Scholar and DBLP.

 

8. "Discovering Top-k Relevant and Diversified Rules." ACM SIGMOD Conference on Management of Data, 2024. (SIGMOD '24)

with Wenfei Fan, Ziyan Han, Min Xie, in alphabetical order.

7. Zhang, Guangyi, Nikolaj Tatti, and Aristides Gionis. "Finding favourite tuples on data streams with provably few comparisons." Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023. (KDD '23, 313/1416 = 22.1%) arXiv:2307.02946. code.

6. Zhang, Guangyi, Nikolaj Tatti, and Aristides Gionis. "Ranking with submodular functions on the fly." Proceedings of the 2023 SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics, 2023. (SDM '23) arXiv:2301.06787. code.

Best paper award (among 459 submissions), kudos my great co-authors!

5. Zhang, Guangyi, Nikolaj Tatti, and Aristides Gionis. "Coresets remembered and items forgotten: submodular maximization with deletions." 22nd IEEE International Conference on Data Mining, 2022. (ICDM '22) arXiv:2203.01241. code.

Accepted as a full paper (9.77%).

4. Zhang, Guangyi, and Aristides Gionis. "Regularized impurity reduction: Accurate decision trees with complexity guarantees." Data Mining and Knowledge Discovery (2022). (DAMI '22, Journal Track of ECML PKDD 2022) link. arXiv:2208.10949. code.

3. Zhang, Guangyi, Nikolaj Tatti, and Aristides Gionis. "Ranking with submodular functions on a budget." Data Mining and Knowledge Discovery (2022). (DAMI '22, Journal Track of ECML PKDD 2022) link. arXiv:2204.04168. code .

2. Zhang, Guangyi, and Aristides Gionis. "Diverse Rule Sets." Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020. (KDD '20) arXiv:2006.09890. code.

1. Zhang, Guangyi, and Aristides Gionis. "Maximizing diversity over clustered data." Proceedings of the 2020 SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics, 2020. (SDM '20) arXiv:2001.03050. code.

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