Zobrazeno 1 - 10
of 1 127
pro vyhledávání: '"Nguyen TA"'
Publikováno v:
International Medical Case Reports Journal, Vol Volume 15, Pp 361-366 (2022)
Hong Duc Pham,1,2 The Anh Nguyen,3 Thi Giang Doan,1,2 Van Giang Bui,2,4 Thanh Van Phan-Nguyen5 1Radiology Department, Saint Paul Hospital of Ha Noi, Ha Noi, Vietnam; 2Radiology Department, Hanoi Medical University, Ha Noi, Vietnam; 3Department of Res
Externí odkaz:
https://doaj.org/article/9de58188f32040d1b4a9109bdbfafe76
Publikováno v:
Patient Preference and Adherence, Vol Volume 15, Pp 2523-2538 (2021)
Nhi Xuan Nguyen,1 Khoa Tran,1 Tuyet Anh Nguyen2 1Faculty of Business Administration, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam; 2Department of Business, Minerva University, San Francisco, CA, USACorrespondence: Khoa TranFaculty of Busine
Externí odkaz:
https://doaj.org/article/1ded1ba320bc4f26b628df9cf8dfbbca
Autor:
Nguyen, Ta Duy, Ene, Alina
We study the densest subgraph problem and give algorithms via multiplicative weights update and area convexity that converge in $O\left(\frac{\log m}{\epsilon^{2}}\right)$ and $O\left(\frac{\log m}{\epsilon}\right)$ iterations, respectively, both wit
Externí odkaz:
http://arxiv.org/abs/2405.18809
Publikováno v:
International Medical Case Reports Journal, Vol Volume 13, Pp 425-430 (2020)
He Van Dong,1,* Van Dinh Tran,1,* Dinh-Hoa Nguyen,2– 4,* Hoe Van Vu,5 Tuan Anh Nguyen,6 Ha Ngoc Thi Doan,7 Hoang-Long Vo7,8 1Department of Neurosurgery I, Viet Duc University Hospital, Hanoi 100000, Vietnam; 2Institute of Orthopedic Trauma, Viet Du
Externí odkaz:
https://doaj.org/article/97a0912197fb4c13ad89eb327e6df85e
Autor:
Nguyen TA, Eichenfield LF
Publikováno v:
Clinical, Cosmetic and Investigational Dermatology, Vol 2015, Iss default, Pp 549-554 (2015)
Tuyet A Nguyen,1,2 Lawrence F Eichenfield1,31Division of Pediatric and Adolescent Dermatology, Rady Children's Hospital, San Diego, CA, 2Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, 3Department of Dermatology, University of
Externí odkaz:
https://doaj.org/article/6b133df352ba48fab1037387ae0305a3
In this work, we study the convergence \emph{in high probability} of clipped gradient methods when the noise distribution has heavy tails, ie., with bounded $p$th moments, for some $1
Externí odkaz:
http://arxiv.org/abs/2304.01119
In this work, we describe a generic approach to show convergence with high probability for both stochastic convex and non-convex optimization with sub-Gaussian noise. In previous works for convex optimization, either the convergence is only in expect
Externí odkaz:
http://arxiv.org/abs/2302.14843
While the convergence behaviors of stochastic gradient methods are well understood \emph{in expectation}, there still exist many gaps in the understanding of their convergence with \emph{high probability}, where the convergence rate has a logarithmic
Externí odkaz:
http://arxiv.org/abs/2302.05437
We study the application of variance reduction (VR) techniques to general non-convex stochastic optimization problems. In this setting, the recent work STORM [Cutkosky-Orabona '19] overcomes the drawback of having to compute gradients of "mega-batche
Externí odkaz:
http://arxiv.org/abs/2209.14853
Existing analysis of AdaGrad and other adaptive methods for smooth convex optimization is typically for functions with bounded domain diameter. In unconstrained problems, previous works guarantee an asymptotic convergence rate without an explicit con
Externí odkaz:
http://arxiv.org/abs/2209.14827