Zobrazeno 1 - 10
of 5 848
pro vyhledávání: '"Scheinberg A"'
Publikováno v:
Journal of Hepatocellular Carcinoma, Vol Volume 6, Pp 167-181 (2019)
Patricia D Jones,1,2 Andrew R Scheinberg,3 Valery Muenyi,3 Joselin Gonzalez-Diaz,1 Paul M Martin,1,2 Erin Kobetz2,4 1Department of Medicine, Division of Gastroenterology and Hepatology, University of Miami Miller School of Medicine, Miami, Florida, U
Externí odkaz:
https://doaj.org/article/4cade1c66c63445c860ab2217f3bda3a
We develop and analyze stochastic variants of ISTA and a full backtracking FISTA algorithms [Beck and Teboulle, 2009, Scheinberg et al., 2014] for composite optimization without the assumption that stochastic gradient is an unbiased estimator. This w
Externí odkaz:
http://arxiv.org/abs/2402.15646
Autor:
Scheinberg, Katya, Xie, Miaolan
We present a high probability complexity bound for a stochastic adaptive regularization method with cubics, also known as regularized Newton method. The method makes use of stochastic zeroth-, first- and second-order oracles that satisfy certain accu
Externí odkaz:
http://arxiv.org/abs/2308.13161
Autor:
Fábio Fernandes, Georgina del Cisne Jadán Luzuriaga, Guilherme Wesley Peixoto da Fonseca, Edileide Barros Correia, Alzira Alves Siqueira Carvalho, Ariane Vieira Scarlatelli Macedo, Otavio Rizzi Coelho-Filho, Phillip Scheinberg, Murillo Oliveira Antunes, Pedro Vellosa Schwartzmann, Sandrigo Mangini, Wilson Marques, Marcus Vinicius Simões
Publikováno v:
Orphanet Journal of Rare Diseases, Vol 19, Iss 1, Pp 1-10 (2024)
Abstract Background Transthyretin amyloidosis (ATTR) is a multisystem disease caused by the deposition of fibrillar protein in organs and tissues. ATTR genotypes and phenotypes are highly heterogeneous. We present data on physical signs and symptoms,
Externí odkaz:
https://doaj.org/article/13652cdb50a54f85899e744d9db684ce
Several classical adaptive optimization algorithms, such as line search and trust region methods, have been recently extended to stochastic settings where function values, gradients, and Hessians in some cases, are estimated via stochastic oracles. U
Externí odkaz:
http://arxiv.org/abs/2303.06838
Queueing systems appear in many important real-life applications including communication networks, transportation and manufacturing systems. Reinforcement learning (RL) framework is a suitable model for the queueing control problem where the underlyi
Externí odkaz:
http://arxiv.org/abs/2206.10073
In this paper, we present convergence guarantees for a modified trust-region method designed for minimizing objective functions whose value and gradient and Hessian estimates are computed with noise. These estimates are produced by generic stochastic
Externí odkaz:
http://arxiv.org/abs/2205.03667
Publikováno v:
Foot & Ankle Orthopaedics, Vol 9 (2024)
Introduction/Purpose: Bunionette deformity affects 23% of the population and has numerous surgical options, including a minimally invasive approach (MIA) to decrease complications. Percutaneous surgery is favored by patients as it decreases pain, inf
Externí odkaz:
https://doaj.org/article/7fa81a9250d3488f991e03c5084a3b08
In this paper, we propose Nesterov Accelerated Shuffling Gradient (NASG), a new algorithm for the convex finite-sum minimization problems. Our method integrates the traditional Nesterov's acceleration momentum with different shuffling sampling scheme
Externí odkaz:
http://arxiv.org/abs/2202.03525
Publikováno v:
Journal of the International Society of Sports Nutrition, Vol 9, Iss Suppl 1, p P13 (2012)
Externí odkaz:
https://doaj.org/article/d1d710fc965d49c1b681571e6f24f629