Yutong Wang

PhD Candidate | University of Michigan | yutongw@umich.edu

Hi! I am a sixth year PhD candidate in Electrical Engineering and Computer Science. My research is in machine learning. I am advised by Clay Scott.

Research interests

• Theory of overparametrized learning
• Ensemble methods
• Quantized neural networks
• Application to high-dimensional genomic data analysis.
• Multiclass classification (SVMs in particular)

Preprints

• Consistent Interpolating Ensembles via the Manifold-Hilbert Kernel
  Yutong Wang and Clayton Scott
  [arXiv]

• Learning from Label Proportions by Learning with Label Noise
  Jianxin Zhang, Yutong Wang, and Clayton Scott
  [arXiv]

Publications

• VC dimension of partially quantized neural networks in the overparametrized regime
  Yutong Wang and Clayton Scott
  ICLR 2022.
  [OpenReview] [arXiv] [Code]
• An exact solver for the Weston-Watkins SVM subproblem
  Yutong Wang and Clayton Scott
  ICML 2021.
  [Paper] [arXiv] [Code]
• Weston-Watkins Hinge Loss and Ordered Partitions
  Yutong Wang and Clayton Scott
  NeurIPS 2020.
  [Paper] [arXiv]
• Hybrid Stem Cell States: Insights Into the Relationship Between Mammary Development and Breast Cancer Using Single-Cell Transcriptomics
  Tasha Thong, Yutong Wang, Michael D. Brooks, Christopher T. Lee, Clayton Scott, Laura Balzano, Max S. Wicha, and Justin A. Colacino
  Frontiers in Cell and Developmental Biology.
  [Paper] [Supporting technical report]

Blog posts

• 2020/12/30 Kernel multiclass support vector machine solvers
• 2020/11/06 The Weston-Watkins SVM dual problem
• 2020/10/14 SVM solver jargons
• 2020/10/02 A non-exhaustive list of SVM solvers