Results 51 to 60 of about 43,512 (302)
On the Rate of Convergence of Greedy Algorithms
Mathematics, 2023 In this paper, a new criterion for the evaluation of the theoretical efficiency of a greedy algorithm is suggested. Using this criterion, we prove some results on the rate of convergence of greedy algorithms, which provide expansions. We consider both the case of Hilbert spaces and the more general case of Banach spaces. The new component of this paper
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Interpolating greedy and reluctant algorithms [PDF]
Optimization Methods and Software, 2005 9 pages.
Pierluigi Contucci +4 more
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The role of miR‐335‐5p in the redifferentiation of BRAF p.V600E thyroid cancers
Molecular Oncology, EarlyView.The BRAF p.V600E mutation promotes thyroid cancer dedifferentiation and radioiodine resistance. Using a network approach, we identified miR‐335‐5p as a key regulator of BRAF‐mutated thyroid tumors. Restoring miR‐335‐5p increased thyroid‐specific gene expression and iodine uptake in cells and organoids.
Valeria Pecce +11 more
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Super greedy type algorithms [PDF]
Advances in Computational Mathematics, 2011 We study greedy-type algorithms such that at a greedy step we pick several dictionary elements contrary to a single dictionary element in standard greedy-type algorithms. We call such greedy algorithms {\it super greedy algorithms}. The idea of picking several elements at a greedy step of the algorithm is not new.
Entao Liu, Vladimir N. Temlyakov
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, 2009 This paper studies heuristics for the minimum labelling spanning tree (MLST) problem. The purpose is to find a spanning tree using edges that are as similar as possible.
Darby-Dowman, K +3 more
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FEBS Open Bio, EarlyView.This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill +4 more
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A greedy stacking algorithm for model ensembling and domain weighting
BMC Research Notes, 2020 Objective Because it is impossible to know which statistical learning algorithm performs best on a prediction task, it is common to use stacking methods to ensemble individual learners into a more powerful single learner.
Christoph F. Kurz +2 more
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Clustering Algorithm Reveals Dopamine‐Motor Mismatch in Cognitively Preserved Parkinson's Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To explore the relationship between dopaminergic denervation and motor impairment in two de novo Parkinson's disease (PD) cohorts. Methods n = 249 PD patients from Parkinson's Progression Markers Initiative (PPMI) and n = 84 from an external clinical cohort.
Rachele Malito +14 more
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Energy-Efficient Chain Formation Algorithm for Data Gathering in Wireless Sensor Networks
International Journal of Distributed Sensor Networks, 2012 In wireless sensor networks, since sensor nodes are distributed in inaccessible regions for data gathering, they need to be operated during an assigned time without battery recharging and relocation.
Se-Jung Lim, Myong-Soon Park
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Optimization of PWSN transmission performance on coal mining face
Gong-kuang zidonghua, 2020 In view of problems of long end-to-end time and high packet loss rate of positioning wireless sensor network (PWSN) on coal mining face, a guaranteed greedy scheduling (GGS) algorithm was proposed to optimize network transmission performance.
FANG Zuhao +3 more
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