Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Fine, Shai"'
The weight decay regularization term is widely used during training to constrain expressivity, avoid overfitting, and improve generalization. Historically, this concept was borrowed from the SVM maximum margin principle and extended to multi-class de
Externí odkaz:
http://arxiv.org/abs/2110.04519
We derive a new margin-based regularization formulation, termed multi-margin regularization (MMR), for deep neural networks (DNNs). The MMR is inspired by principles that were applied in margin analysis of shallow linear classifiers, e.g., support ve
Externí odkaz:
http://arxiv.org/abs/2009.06011
We present a selective sampling method designed to accelerate the training of deep neural networks. To this end, we introduce a novel measurement, the minimal margin score (MMS), which measures the minimal amount of displacement an input should take
Externí odkaz:
http://arxiv.org/abs/1911.06996
Common medical conditions are often associated with sleep abnormalities. Patients with medical disorders often suffer from poor sleep quality compared to healthy individuals, which in turn may worsen the symptoms of the disorder. Accurate detection o
Externí odkaz:
http://arxiv.org/abs/1802.07945
Deep convolutional network has been the state-of-the-art approach for a wide variety of tasks over the last few years. Its successes have, in many cases, turned it into the default model in quite a few domains. In this work, we will demonstrate that
Externí odkaz:
http://arxiv.org/abs/1802.05187
Autor:
Zalman, Dana1,2 (AUTHOR) dana.oshri@post.runi.ac.il, Fine, Shai2 (AUTHOR)
Publikováno v:
Entropy. Oct2023, Vol. 25 Issue 10, p1468. 29p.
Autor:
Wimpfheimer, Ariel, Ginosar, Yehuda, Fein, Shai, Goldberger, Esty, Weissman, Charles, Abd-Al-Halim, Haled, Abu-Rais, Hakeem, Berkenstadt, Chaim, Chernoy, Ilya, Armaly, Maruan, Duvdivani, Yaakov, Eidelman, Leonid, Fine, Shai, Fredman, Brian, Gadulov, Yulia, Goldik, Zeev, Gozal, Yaakov, Haituv, Zoya, Izakson, Alex, Katz, Yaakov
Publikováno v:
Israel Journal of Health Policy Research; 9/17/2024, Vol. 13 Issue 1, p1-9, 9p
We consider the problem of PAC-learning from distributed data and analyze fundamental communication complexity questions involved. We provide general upper and lower bounds on the amount of communication needed to learn well, showing that in addition
Externí odkaz:
http://arxiv.org/abs/1204.3514
Autor:
Wimpfheimer, Ariel, Weissman, Charles, Fein, Shai, Ginosar, Yehuda, Abd-Al-Halim, Haled, Abu-Rais, Hakeem, Berkenstadt, Chaim, Chernoy, Ilya, Armaly, Maruan, Duvdivani, Yaakov, Eidelman, Leonid, Fine, Shai, Fredman, Brian, Gadulov, Yulia, Goldik, Zeev, Gozal, Yaakov, Haituv, Zoya, Izakson, Alex, Katz, Yaakov, Matot, Idit
Publikováno v:
Israel Journal of Health Policy Research; 3/2/2023, Vol. 12 Issue 1, p1-11, 11p
Publikováno v:
In Theoretical Computer Science 2008 404(3):219-234