Results 51 to 60 of about 522,654 (284)
An Efficient Line Search Algorithm for Large Scale Optimization [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2010 In this work we present a new algorithm of gradient descent type, in which the stepsize is computed by means of simple approximation of the Hessian Matrix to solve nonlinear unconstrained optimization function.
Abbas Al-Bayati, Ivan Latif
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From Gap-ETH to FPT-Inapproximability: Clique, Dominating Set, and More
, 2017 We consider questions that arise from the intersection between the areas of polynomial-time approximation algorithms, subexponential-time algorithms, and fixed-parameter tractable algorithms.
Chalermsook, Parinya +6 more
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Molecular Oncology, EarlyView.A‐to‐I editing of miRNAs, particularly miR‐200b‐3p, contributes to HGSOC progression by enhancing cancer cell proliferation, migration and 3D growth. The edited form is linked to poorer patient survival and the identification of novel molecular targets.
Magdalena Niemira +14 more
wiley +1 more source
Algorithms, 2022 The article offers a possible treatment for the numerical research of tasks which require searching for an absolute optimum. This approach is established by employing both globalized nature-inspired methods as well as local descent methods for ...
Pavel Sorokovikov, Alexander Gornov
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Handling convexity-like constraints in variational problems
, 2014 We provide a general framework to construct finite dimensional approximations of the space of convex functions, which also applies to the space of c-convex functions and to the space of support functions of convex bodies.
Mérigot, Quentin, Oudet, Edouard
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Molecular Oncology, EarlyView.A comprehensive genomic and proteomic analysis of cervical cancer revealed STK11 and STX3 as a potential biomarkers of chemoradiation resistance. Our study demonstrated EGFR as a therapeutic target, paving the way for precision strategies to overcome treatment failure and the DNA repair pathway as a critical mechanism of resistance.
Janani Sambath +13 more
wiley +1 more source
Mathematical Modeling on a Physics-Informed Radial Basis Function Network
MathematicsThe article is devoted to approximate methods for solving differential equations. An approach based on neural networks with radial basis functions is presented. Neural network training algorithms adapted to radial basis function networks are proposed, in
Dmitry Stenkin, Vladimir Gorbachenko
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Aggressive prostate cancer is associated with pericyte dysfunction
Molecular Oncology, EarlyView.Tumor‐produced TGF‐β drives pericyte dysfunction in prostate cancer. This dysfunction is characterized by downregulation of some canonical pericyte markers (i.e., DES, CSPG4, and ACTA2) while maintaining the expression of others (i.e., PDGFRB, NOTCH3, and RGS5).
Anabel Martinez‐Romero +11 more
wiley +1 more source
Exploring Chebyshev polynomial approximations: Error estimates for functions of bounded variation
AIMS MathematicsApproximation theory plays a central role in numerical analysis, evolving through a variety of methodologies, with significant contributions from Lebesgue, Weierstrass, Fourier, and Chebyshev approximations. For sufficiently smooth functions, the partial
S. Akansha, Aditya Subramaniam
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Almost-Smooth Histograms and Sliding-Window Graph Algorithms
, 2020 We study algorithms for the sliding-window model, an important variant of the data-stream model, in which the goal is to compute some function of a fixed-length suffix of the stream.
Krauthgamer, Robert, Reitblat, David
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