Yutong Wang

  • Assistant Professor of Computer Science

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Education

  • Ph.D. Electrical & Computer Engineering,  University of Michigan, Ann Arbor
  • M.A. Mathematics, University of California, Davis
  • B.S.E. Electrical Engineering, University of Michigan, Ann Arbor

Research Interests

Awards

  • UM Postdoctoral Association Conference Award, 2023
  • NeurIPS Scholar Award, 2022
  • Honorable Mention for Outstanding Graduate Student Instructors and Instructional Aides NIH-sponsored travel award for NeurIPS Conference workshop, 2021
  • NeurIPS 2019 Conference workshop: “Learning Meaningful Representations of Life,” 2019
  • The Rollin M. Gerstacker Foundation Fellowship, 2016
     

Publications

  1. Yutong Wang and Clayton Scott. “Unified Binary and Multiclass Margin-Based Classification”. Journal of Machine Learning Research 25.143 (2024) pp. 1–51.
  2. Pengyu Li , Xiao Li , Yutong Wang, and Qing Qu. “Neural Collapse in Multi-label Learning with Pick-all-label Loss”. International Conference on Machine Learning. 2024.
  3. Yutong Wang, Rishi Sonthalia, and Wei Hu. “Near-Interpolators: Rapid Norm Growth and the Trade-Off be- tween Interpolation and Generalization”. Artificial Intelligence and Statistics. 2024.
  4. Zhiwei Xu, Yutong Wang, Spencer Frei, Gal Vardi, and Wei Hu. “Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data”. International Conference on Learning Representations. 2024.
  5. Yutong Wang and Clayton Scott. “On Classification-Calibration of Gamma-Phi Losses”. Conference on Learning Theory. 2023.
  6. Yutong Wang and Clayton Scott. “Consistent Interpolating Ensembles via the Manifold-Hilbert Kernel”. Neural Information Processing Systems. 2022.
  7. Jianxin Zhang, Yutong Wang, and Clayton Scott. “Learning from Label Proportions by Learning with Label Noise”. Neural Information Processing Systems. 2022.
  8. Yutong Wang and Clayton Scott. “VC dimension of partially quantized neural networks in the overparametrized regime”. International Conference on Learning Representations. 2022.
  9. Yutong Wang and Clayton Scott. “An exact solver for the Weston-Watkins SVM subproblem”. In: International Conference on Machine Learning. 2021.
  10. Yutong Wang and Clayton Scott. “Weston-Watkins Hinge Loss and Ordered Partitions”. In: Neural Informa- tion Processing Systems. 2020.
  11. Tasha Thong, Yutong Wang, Michael Brooks, Christopher Lee, Clayton Scott, Laura Balzano, Max Wicha, and Justin Colacino. “Hybrid stem cell states: insights into the relationship between mammary development and breast cancer using single-cell transcriptomics”. In: Frontiers in Cell and Developmental Biology 8 (2020), p. 288.

Grants

NSF CISE Medium, Award # 2312842 Collaborative Research: RI: Medium: Principles for Optimization, Generalization, and Transferability via Deep Neural Collapse, Budget: $1,200,000, Period Covered: 10/01/2023 - 09/30/2026 PI: Zhihui Zhu, Co-PI: Jeremias Sulam, Co-PI: Qing Qu, Senior Personnel: Yutong Wang