Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox

The Power and Limitation of Pretraining-Finetuning for Linear Regression under Covariate Shift


Aug 03, 2022
Jingfeng Wu, Difan Zou, Vladimir Braverman, Quanquan Gu, Sham M. Kakade

* 32 pages, 1 figure, 1 table 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Pretrained Models for Multilingual Federated Learning


Jun 06, 2022
Orion Weller, Marc Marone, Vladimir Braverman, Dawn Lawrie, Benjamin Van Durme

* NAACL 2022 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Sparsity and Heterogeneous Dropout for Continual Learning in the Null Space of Neural Activations


Mar 12, 2022
Ali Abbasi, Parsa Nooralinejad, Vladimir Braverman, Hamed Pirsiavash, Soheil Kolouri


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

New Coresets for Projective Clustering and Applications


Mar 08, 2022
Murad Tukan, Xuan Wu, Samson Zhou, Vladimir Braverman, Dan Feldman


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Risk Bounds of Multi-Pass SGD for Least Squares in the Interpolation Regime


Mar 07, 2022
Difan Zou, Jingfeng Wu, Vladimir Braverman, Quanquan Gu, Sham M. Kakade

* 28 pages, 2 figures 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Cross-Domain Federated Learning in Medical Imaging


Dec 18, 2021
Vishwa S Parekh, Shuhao Lai, Vladimir Braverman, Jeff Leal, Steven Rowe, Jay J Pillai, Michael A Jacobs

* Under Review for MIDL 2022 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Last Iterate Risk Bounds of SGD with Decaying Stepsize for Overparameterized Linear Regression


Oct 12, 2021
Jingfeng Wu, Difan Zou, Vladimir Braverman, Quanquan Gu, Sham M. Kakade

* 40 pages, 2 figures 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Gap-Dependent Unsupervised Exploration for Reinforcement Learning


Aug 11, 2021
Jingfeng Wu, Vladimir Braverman, Lin F. Yang


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

The Benefits of Implicit Regularization from SGD in Least Squares Problems


Aug 10, 2021
Difan Zou, Jingfeng Wu, Vladimir Braverman, Quanquan Gu, Dean P. Foster, Sham M. Kakade

* 39 pages, 1 figure 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Adversarial Robustness of Streaming Algorithms through Importance Sampling


Jun 28, 2021
Vladimir Braverman, Avinatan Hassidim, Yossi Matias, Mariano Schain, Sandeep Silwal, Samson Zhou


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email
1
2
3
>>