Xiao Li (李虓) 个人学术档案

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	总计	2019 年至今
引用	393	393
h 指数	7	7
i10 指数	7	7

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Qing QuAssistant Professor, Dept. of EECS, University of Michigan在 umich.edu 的电子邮件经过验证
Zhihui ZhuAssistant Professor, Ohio State University在 osu.edu 的电子邮件经过验证
Chong YouGoogle在 google.com 的电子邮件经过验证
Jinxin ZhouOhio State University在 osu.edu 的电子邮件经过验证
Tianyu Ding, Ph.D.Senior Researcher, Microsoft | Johns Hopkins University在 microsoft.com 的电子邮件经过验证
Sheng LiuStanford University在 stanford.edu 的电子邮件经过验证
Yuexiang ZhaiUC Berkeley在 berkeley.edu 的电子邮件经过验证
Jeremias SulamAssistant Professor, BME, Johns Hopkins University在 jhu.edu 的电子邮件经过验证
Carlos Fernandez-GrandaCourant Institute and Center for Data Science, New York University在 cims.nyu.edu 的电子邮件经过验证
Kangning LiuAdobe Inc在 adobe.com 的电子邮件经过验证
Tingting WuImaging Scientist at Metalenz在 wustl.edu 的电子邮件经过验证
Matthew D. LewAssociate Professor of Electrical and Systems Engineering, Washington University in St. Louis在 wustl.edu 的电子邮件经过验证
Can YarasPhD Student, University of Michigan在 umich.edu 的电子邮件经过验证
PENG WANGPostdoc Fellow, Department of Electrical Engineering and Computer Science, University of Michigan在 umich.edu 的电子邮件经过验证
Wei HuAssistant Professor of Computer Science and Engineering, University of Michigan在 umich.edu 的电子邮件经过验证
Yutong WangPostdoctoral Research Fellow, University of Michigan在 umich.edu 的电子邮件经过验证
Yen-Chang HsuSamsung Research America在 gatech.edu 的电子邮件经过验证
Yilin ShenAI Research Scientist在 samsung.com 的电子邮件经过验证
Ting HuaSamsung Research America在 vt.edu 的电子邮件经过验证
Shangqian GaoUniversity of Pittsburgh; Samsung Research America在 pitt.edu 的电子邮件经过验证

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Xiao Li (李虓)

Ph.D. candidate at University of Michigan

在 umich.edu 的电子邮件经过验证 - 首页

Representation Learning Machine Learning


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
A geometric analysis of neural collapse with unconstrained features Z Zhu, T Ding, J Zhou, X Li, C You, J Sulam, Q Qu Advances in Neural Information Processing Systems 34, 29820-29834, 2021	150	2021
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features J Zhou, X Li, T Ding, C You, Q Qu, Z Zhu arXiv preprint arXiv:2203.01238, 2022	79	2022
Investigating the catastrophic forgetting in multimodal large language models Y Zhai, S Tong, X Li, M Cai, Q Qu, YJ Lee, Y Ma arXiv preprint arXiv:2309.10313, 2023	51	2023
Are all losses created equal: A neural collapse perspective J Zhou, C You, X Li, K Liu, S Liu, Q Qu, Z Zhu Advances in Neural Information Processing Systems 35, 31697-31710, 2022	45	2022
Convolutional normalization: Improving deep convolutional network robustness and training S Liu, X Li, Y Zhai, C You, Z Zhu, C Fernandez-Granda, Q Qu Advances in Neural Information Processing Systems 34, 28919-28928, 2021	24	2021
Principled and Efficient Transfer Learning of Deep Models via Neural Collapse X Li, S Liu, J Zhou, X Lu, C Fernandez-Granda, Z Zhu, Q Qu arXiv preprint arXiv:2212.12206, 2022	21	2022
Deep-SMOLM: deep learning resolves the 3D orientations and 2D positions of overlapping single molecules with optimal nanoscale resolution T Wu, P Lu, MA Rahman, X Li, MD Lew Optics Express 30 (20), 36761-36773, 2022	11	2022
Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination P Wang, X Li, C Yaras, Z Zhu, L Balzano, W Hu, Q Qu arXiv preprint arXiv:2311.02960, 2023	7	2023
Neural collapse in multi-label learning with pick-all-label loss P Li, X Li, Y Wang, Q Qu arXiv preprint arXiv:2310.15903, 2023	3	2023
Dynamic Low-rank Estimation for Transformer-based Language Models T Hua, X Li, S Gao, YC Hsu, Y Shen, H Jin Findings of the Association for Computational Linguistics: EMNLP 2023, 9275-9287, 2023	2	2023

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