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This paper proposes a family of line-search methods to deal with weighted orthogonal procrustes problems. In particular, the proposed family uses a search direction based on a convex combination ...
Landslide prediction necessitates viewing the past, present, and future states of a slope as a constantly changing dialectical unity, with prediction laws derived from known past and present ...
Abstract: This article investigates distributed finite-time optimization problems for first-order multi-agent systems (MASs) with time-varying cost functions under arbitrary strongly connected ...
Coronavirus disease 2019 (COVID-19) continuously progresses despite the application of a variety of vaccines. Therefore, it is still imperative to find effective ways for treating COVID-19. Recent ...
One key ingredient in deep learning is the stochastic gradient descent (SGD) algorithm, which allows neural nets to find generalizable solutions at flat minima of the high-dimensional loss function.
Partial differential equations (PDEs) are among the most ubiquitous tools used in modeling problems in nature. However, solving high-dimensional PDEs has been notoriously difficult due to the “curse ...
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