Results 71 to 80 of about 53,358 (305)
Fast Matrix Multiplication with Big Sparse Data
Cybernetics and Information Technologies, 2017 Big Data becameabuzz word nowadays due to the evolution of huge volumes of data beyond peta bytes. This article focuses on matrix multiplication with big sparse data.
Somasekhar G., Karthikeyan K.
doaj +1 more source
Peripheral Neutrophil Activation and Extracellular Trap Formation in Amyotrophic Lateral Sclerosis
Annals of Clinical and Translational Neurology, EarlyView.Markers of neutrophil activation are increased in plasma during ALS, and markers of NET formation associate with ALS survival. ABSTRACT Objectives Peripheral neutrophil levels in amyotrophic lateral sclerosis (ALS) inversely correlate with survival, suggesting a role for neutrophils in disease progression.
Lillia A. Baird +9 more
wiley +1 more source
GPU computing performance analysis on matrix multiplication
The Journal of Engineering, 2019 The machine learning has been widely used in intelligent data mining. The high-computational complexity of machine learning and huge data volume present challenges to computing platforms.
Zhibin Huang +3 more
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Gaussian Processes and Fast Matrix-Vector Multiplies [PDF]
, 2009 Gaussian processes (GPs) provide a flexible framework for probabilistic regression. The necessary computations involve standard matrix operations.
Murray, Iain, Murray, Iain; id_orcid
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Matrix Multiplication Using Only Addition
, 2023 Matrix multiplication consumes a large fraction of the time taken in many machine-learning algorithms. Thus, accelerator chips that perform matrix multiplication faster than conventional processors or even GPU's are of increasing interest. In this paper,
Cussen, Daniel, Ullman, Jeffrey D.
core
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objectives Focal cortical dysplasia (FCD) is the most common etiology of drug‐resistant epilepsy in children. Focal to bilateral tonic–clonic seizures (FBTCS) mark a high risk of drug‐resistant epilepsy and involve thalamocortical circuitry in their generation and propagation.
Hua Xie +8 more
wiley +1 more source
Quantum Subroutine for Efficient Matrix Multiplication
IEEE AccessWe propose an efficient quantum subroutine for matrix multiplication that computes a state vector encoding the entries of the product of two matrices in superposition.
Anna Bernasconi +3 more
doaj +1 more source
Arthritis Care &Research, EarlyView.Objective This study aimed to characterize cannabis product choices (cannabinoid content and formulation) among patients with rheumatologic conditions and their associations with patient factors, patient‐reported perceived side effects, and positive impacts.
Susan Zhang +10 more
wiley +1 more source
Analysis of high performance sparse matrix-vector multiplication for small finite fields
, 2020 Saunders, B. DavidThis thesis explores the intricacies of obtaining high performance sparse matrix-vector multiplication on modern hardware, with an emphasis on operating over data from small finite fields.
Lambert, Matthew A.
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A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam +2 more
wiley +1 more source