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Minimizing Data Movement and Parameter Count Across the Machine Learning Stack de Andrew Sabot

Minimizing Data Movement and Parameter Count Across the Machine Learning Stack: Synthesis Lectures on Computer Science

Autor Andrew Sabot
en Limba Engleză Hardback – 4 aug 2026

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Specificații

ISBN-13: 9783032230997
ISBN-10: 3032230993
Pagini: 128
Dimensiuni: 173 x 246 x 13 mm
Greutate: 0.35 kg
Editura: Springer
Colecția Synthesis Lectures on Computer Science
Seria Synthesis Lectures on Computer Science

Notă biografică

Andrew Sabot, Ph.D., is a Software Engineer working on Machine Learning at Google. He received his Ph.D. (2025) and M.S. (2021) in Computer Science from Harvard University. Dr. Sabot’s work focuses on the intersection of hardware-aware kernels, model compression, and transformer inference acceleration to enable the sustainable deployment of state-of-the-art AI.