侍蒋鑫 Jiang-Xin Shi Ph.D. Student LAMDA Group School of Artificial Intelligence National Key Laboratory for Novel Software Technology Nanjing University, Nanjing 210023, China. Supervisor: Professor Yu-Feng Li Email: shijx@lamda.nju.edu.cn

Biography

• Currently, I am a first year Ph.D. student from School of Artificial Intelligence in Nanjing University. I am also a member of LAMDA Group, which is led by professor Zhi-Hua Zhou.

• Before this, I received my B.Sc. degree from School of Computer Science, Northwestern Polytechnical University in July 2020. In the same year, I was admitted to study for a M.Sc. degree in Department of Computer Science and Technology, Nanjing University without entrance examination.

Research Interests

My research interests include Machine Learning and Data Mining.

Specifically, I am interested in Long-Tailed Learning. Here is a repository maintained by Dr. Tong Wei: [Awesome Long-Tailed Learning]

Publications

(* denotes the co-first authors)

• Parameter-Efficient Long-Tailed Recognition. [pdf] [arxiv] [code]
  Jiang-Xin Shi*, Tong Wei*, Zhi Zhou, Xin-Yan Han, Jie-Jing Shao, Yu-Feng Li.
  Preprint.

• How Re-sampling Helps for Long-Tail Learning? [pdf] [code]
  Jiang-Xin Shi*, Tong Wei*, Yuke Xiang, Yu-Feng Li.
  The 37th Conference on Neural Information Processing Systems (NeurIPS 2023).

• Residual Diverse Ensemble for Long-Tailed Multi-Label Text Classification.
  Jiang-Xin Shi*, Tong Wei*, Yu-Feng Li.
  SCIENCE CHINA Information Sciences (SCIS). In Press.

• A Survey on Extreme Multi-label Learning. [arxiv]
  Tong Wei, Zhen Mao, Jiang-Xin Shi, Yu-Feng Li, Min-Ling Zhang.
  Preprint.

• Transfer and Share: Semi-Supervised Learning from Long-Tailed Data. [pdf] [code]
  Tong Wei*, Qian-Yu Liu*, Jiang-Xin Shi, Wei-Wei Tu, Lan-Zhe Guo.
  Machine Learning (MLJ).

• Prototypical Classifier for Robust Class-Imbalanced Learning. [pdf] [code]
  Tong Wei*, Jiang-Xin Shi*, Yu-Feng Li, Min-Ling Zhang.
  The 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2022).
  (PAKDD 2022 Best Paper Award)

• Robust Long-Tailed Learning under Label Noise. [arxiv] [code]
  Tong Wei*, Jiang-Xin Shi*, Wei-Wei Tu, Yu-Feng Li.
  Preprint.

• Probabilistic Label Tree for Streaming Multi-Label Learning. [pdf] [code]
  Tong Wei*, Jiang-Xin Shi*, Yu-Feng Li.
  The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2021).

Awards & Honors

• PAKDD Best Paper Award, 2022

• Outstanding Graduate of Northwestern Polytechnical University, 2020

• CCF Elite Collegiate Award, 2019

• ACM-ICPC Asia Regional Contest Gold Medal, 2018 and 2017

• National Scholarship, 2018 and 2017

Services

• Reviewer for Conferences: ICML 2023; NeurIPS 2023; ICLR 2024; AAAI 2023, 2024, ECAI 2023, ACML 2022.

• Reviewer for Journal: Machine Learning.

• Teaching Assistant for Introduction to Advanced Machine Learning, Nanjing Univeristy, Spring, 2022

• Teaching Assistant for Introduction to Machine Learning, Nanjing Univeristy, Fall, 2021

• Captain of Northwestern Polytechnical University ACM-ICPC Competition Team, 2018

Correspondence

Email: shijx@lamda.nju.edu.cn

Laboratory: Room 113, Computer Science Building, Nanjing University Xianlin Campus, Nanjing, China