1 paper published in TMLR

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Our paper on a local Polyak-Lojasiewicz condition and descent lemma of gradient descent for overparametrized linear models [1] has been published in Transactions on Machine Learning Research. Congrats Ziqing!

[1] Z. Xu, H. Min, S. Tarmoun, E. Mallada, and R. Vidal, “A Local Polyak-Łojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models,” Transaction on Machine Learning Research (TMLR), 2025.
[Bibtex] [Download PDF] 
@article{xmtmv2025tmlr,
  author = {Xu, Ziqing and Min, Hancheng and Tarmoun, Salma and Mallada, Enrique and Vidal, Rene},
  grants = {Global Centers-2330450},
  issn = {2835-8856},
  journal = {Transaction on Machine Learning Research (TMLR)},
  month = {5},
  record = {accepted May 2025, submitted Feb 2025},
  title = {A Local Polyak-Łojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models},
  url = {https://mallada.ece.jhu.edu/pubs/2025-TMLR-XMTMV.pdf},
  year = {2025}
}