I am a final-year Ph.D. student in Computer Sciences at the University of Wisconsin-Madison. I am advised by Robert Nowak. In Summer 2021, I was a research intern at Microsoft Research NYC.

I am on the 2022-2023 job market.

I am broadly interested in interactive machine learning, where my goal is to achieve data efficiency by designing novel human-in-the-loop learning algorithms and systems. I study fundamental interactive learning paradigms such as active learning, bandits, and reinforcement learning, and I pay particular attention to incorporating deep learning into these learning paradigms. I also explore the connections between interactive machine learning and systems and actively participate in interdisciplinary collaborations.

Publications

• Active Learning with Neural Networks: Insights from Nonparametric Statistics
  Yinglun Zhu and Robert Nowak
  Conference on Neural Information Processing Systems (NeurIPS), 2022

• Efficient Active Learning with Abstention
  Yinglun Zhu and Robert Nowak
  Conference on Neural Information Processing Systems (NeurIPS), 2022

• Contextual Bandits with Large Action Spaces: Made Practical
  Yinglun Zhu, Dylan Foster, John Langford, and Paul Mineiro
  International Conference on Machine Learning (ICML), 2022, Spotlight, 6 min

• Contextual Bandits with Smooth Regret: Computational Efficiency in Continuous Action Spaces
  Yinglun Zhu and Paul Mineiro
  International Conference on Machine Learning (ICML), 2022, Oral, 17 min (top 2.1%)

• Near Instance Optimal Model Selection for Pure Exploration Linear Bandits
  Yinglun Zhu, Julian Katz-Samuels, and Robert Nowak
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2022

• Pareto Optimal Model Selection in Linear Bandits
  Yinglun Zhu and Robert Nowak
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2022

• Pure Exploration in Kernel and Neural Bandits
  Yinglun Zhu\(^\star\), Dongruo Zhou\(^\star\), Ruoxi Jiang\(^\star\), Quanquan Gu, Rebecca Willett, and Robert Nowak
  Conference on Neural Information Processing Systems (NeurIPS), 2021

• On Regret with Multiple Best Arms
  Yinglun Zhu and Robert Nowak
  Conference on Neural Information Processing Systems (NeurIPS), 2020

• Robust Outlier Arm Identification
  Yinglun Zhu, Sumeet Katariya, and Robert Nowak
  International Conference on Machine Learning (ICML), 2020

Professional Services

• Co-organizer: SILO Seminar at UW-Madison

• Journal reviewer:

  • Journal of Machine Learning Research (JMLR)

  • Transactions on Machine Learning Research (TMLR)

• Conference reviewer: ICML, NeurIPS (Outstanding Reviewer Award in 2021), ICLR, AISTATS, ISIT
  

Teaching Experiences

• Teaching Assistant at UW-Madison:
  

  • CS/ECE 761 Mathematical Foundations of Machine Learning, Spring 2022, Spring 2020 (Head TA)

  • CS/ECE/ME 532 Matrix Methods in Machine Learning, Fall 2019

  • CS 412 Introduction to Numerical Methods, Fall 2018

  • CS/MATH 513 Numerical Linear Algebra, Spring 2018