Results 61 to 70 of about 9,831,579 (305)
Randomized Quasi-Newton Updates Are Linearly Convergent Matrix Inversion Algorithms [PDF]
SIAM Journal on Matrix Analysis and Applications, 2016 We develop and analyze a broad family of stochastic/randomized algorithms for calculating an approximate inverse matrix. We also develop specialized variants maintaining symmetry or positive definiteness of the iterates.
R. Gower, Peter Richtárik
semanticscholar +1 more source
ATF4‐mediated stress response as a therapeutic vulnerability in chordoma
Molecular Oncology, EarlyView.We screened 5 chordoma cell lines against 100+ inhibitors of epigenetic and metabolic pathways and kinases and identified halofuginone, a tRNA synthetase inhibitor. Mechanistically halofuginone induces an integrated stress response, with eIF2alpha phosphorylation, activation of ATF4 and its target genes CHOP, ASNS, INHBE leading to cell death ...
Lucia Cottone +11 more
wiley +1 more source
Block Row Kronecker-Structured Linear Systems With a Low-Rank Tensor Solution
Frontiers in Applied Mathematics and Statistics, 2022 Several problems in compressed sensing and randomized tensor decomposition can be formulated as a structured linear system with a constrained tensor as the solution.
Stijn Hendrikx +3 more
doaj +1 more source
On Randomized Algorithms for Matching in the Online Preemptive Model [PDF]
Embedded Systems and Applications, 2014 We investigate the power of randomized algorithms for the maximum cardinality matching (MCM) and the maximum weight matching (MWM) problems in the online preemptive model.
Ashish Chiplunkar +2 more
semanticscholar +1 more source
LDAcoop: Integrating non‐linear population dynamics into the analysis of clonogenic growth in vitro
Molecular Oncology, EarlyView.Limiting dilution assays (LDAs) quantify clonogenic growth by seeding serial dilutions of cells and scoring wells for colony formation. The fraction of negative wells is plotted against cells seeded and analyzed using the non‐linear modeling of LDAcoop.
Nikko Brix +13 more
wiley +1 more source
Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?
Machine Learning and Knowledge Extraction, 2020 Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem.
Joakim Linja +3 more
doaj +1 more source
A Multi-Start Biased-Randomized Algorithm for the Capacitated Dispersion Problem
Mathematics, 2022 The capacitated dispersion problem is a variant of the maximum diversity problem in which a set of elements in a network must be determined. These elements might represent, for instance, facilities in a logistics network or transmission devices in a ...
Juan F. Gomez +4 more
doaj +1 more source
Molecular Oncology, EarlyView.Nanosecond infrared laser (NIRL) low‐volume sampling combined with shotgun lipidomics uncovers distinct lipidome alterations in oropharyngeal squamous cell carcinoma (OPSCC) of the palatine tonsil. Several lipid species consistently differentiate tumor from healthy tissue, highlighting their potential as diagnostic markers.
Leonard Kerkhoff +11 more
wiley +1 more source
A New Randomized Algorithm for Handling Scheduling Conflicts in Grids
Advances in Electrical and Computer Engineering, 2009 As the scale of Grid platforms grows, the idea of a centralized scheduler loses its efficiency, and it is replaced with the scheme of decentralized schedulers.
VAHDAT-NEJAD, H., ZAMANIFAR, K.
doaj +1 more source
Algorithms with greedy heuristic procedures for mixture probability distribution separation [PDF]
Yugoslav Journal of Operations Research, 2019 For clustering problems based on the model of mixture probability distribution separation, we propose new Variable Neighbourhood Search algorithms (VNS) and evolutionary genetic algorithms (GA) with greedy agglomerative heuristic procedures and compare ...
Kazakovtsev Lev +3 more
doaj +1 more source