Shen-Huan Lyu（吕沈欢）

Shen-Huan Lyu [简历 & Resume] Ph.D. from LAMDA Group Department of Computer Science and Technology National Key Laboratory for Novel Software Technology Nanjing University Laboratory: 912,Building of Computer Science and Technology, Xianlin Campus of Nanjing University email: lvsh at lamda.nju.edu.cn

[Update, 2023] Now, I am an Assistant Researcher in College of Computer and Information at Hohai University. This is my new Homepage.

[Update, 2022] On 18/11/2022, I have defended my Ph.D. dissertation, and became a Ph.D.

[Update, 2017] On 01/09/2017, I joined the Department of Computer Science and Technology in Nanjing University as a Ph.D. student and a member of LAMDA Group, led by professor Zhi-Hua Zhou.

Biography

Research Interest

• Deep Forest
• Deep Neural Network
• Open Environment Machine Learning

Publications

• [NeurIPS 2022 Oral] Depth is More Powerful than Width with Prediction Concatenation in Deep Forest. [pdf] [bib]
  Shen-Huan Lyu, Yi-Xiao He, and Zhi-Hua Zhou.
  In: Advances in Neural Information Processing Systems 35, New Orleans, Louisiana, US, 2022.


• [NN 2022] Improving Generalization of Neural Networks by Leveraging Margin Distribution. [pdf] [code] [arXiv] [bib]
  Shen-Huan Lyu, Lu Wang, and Zhi-Hua Zhou.
  Neural Networks, 151:48-60, 2022.


• [CJE 2022] A Region-Based Analysis for the Feature Concatenation in Deep Forests. [pdf] [bib]
  Shen-Huan Lyu, Yi-He Chen, and Zhi-Hua Zhou.
  Chinese Journal of Electronics, 2022.


• [JOS 2022] 基于交互表示的多标记深度森林方法. [pdf] [code] [bib]
  吕沈欢, 陈一赫, 姜远.
  软件学报, 2022.


• [ICDM 2021] Improving Deep Forest by Exploiting High-Order Interactions. [pdf] [code] [poster] [video] [bib]
  Yi-He Chen*, Shen-Huan Lyu*, and Yuan Jiang (* indicates equal contribution).
  In: Proceedings of the 21st IEEE International Conference on Data Mining, pp. 1030-1035, Auckland, NZ, 2021.


• [NeurIPS 2019] A Refined Margin Distribution Analysis for Forest Representation Learning. [pdf] [code] [poster] [arXiv] [bib]
  Shen-Huan Lyu, Liang Yang, and Zhi-Hua Zhou.
  In: Advances in Neural Information Processing Systems 32, pp. 5531-5541, Vancouver, British Columbia, CA, 2019.

Technical Blog

• Shell Coding
  
• Introduction to Deep Forest
  
• Consistency of Random Forest
  
• Depth Separation in Neural Network

Teaching Assistant

• LAMDA-1 Theory Seminar. (Topics: Generalization, Consistency, Representation and Diversity; Spring, 2022.)
• C++ Programming. (With Prof. Hao Hu; For Undergraduate Students, Spring, 2019)
• LAMDA Machine Learning Summer Seminar. (For New Students in LAMDA, Summer, 2018)
• Introduction to Machine Learning. (With Prof. Zhi-Hua Zhou; For Undergraduate Students, Spring, 2018)

Academic Service

• ICML: 2021, 2022
• NeurIPS: 2020,2021, 2022
• AAAI: 2020, 2021
• IJCAI: 2020, 2021, 2022
• ICLR: 2020, 2021
• AISTATS: 2020

• Artificial Intelligence (AIJ)
• IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
• IEEE Transactions on Knowledge and Data Engineering (TKDE)
• IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
• ACM Transactions on Knowledge Discovery from Data (TKDD)
• Machine Learning (MLJ)

Awards & Honors

• The Second Class Academic Scholarship in Nanjing University , Nanjing, 2020

• Artificial Intelligence Scholarship in Nanjing University , Nanjing, 2019

• The First Class Academic Scholarship in Nanjing University , Nanjing, 2019

• The First Class Academic Scholarship in Nanjing University , Nanjing, 2018

• Presidential Special Scholarship for first year Ph.D. Student in Nanjing University , Nanjing, 2017

• The University Silver Prize Scholarship for Excellent Student in University of Science and Technology of China , Hefei, 2016

• The University Silver Prize Scholarship for Excellent Student in University of Science and Technology of China , Hefei, 2014