Sparsifying vectors for neural network models based on overlapping windows

Embodiments of the present disclosure include systems and methods for sparsifying vectors for neural network models based on overlapping windows. A window is used to select a first set of elements in a vector of elements. A first element is selected from the first set of elements having the highest...

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Bibliographische Detailangaben
Hauptverfasser:	VARATKAR, GIRISH VISHNU, MORE, ANKIT, AGRAWAL, GAURAV, HEDDES, MATTHEUS C, DARVISH ROUHANI, BITA
Format:	Patent
Sprache:	chi ; eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING IMAGE DATA PROCESSING OR GENERATION, IN GENERAL INFORMATION STORAGE PHYSICS STATIC STORES
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Zusammenfassung:	Embodiments of the present disclosure include systems and methods for sparsifying vectors for neural network models based on overlapping windows. A window is used to select a first set of elements in a vector of elements. A first element is selected from the first set of elements having the highest absolute value. The window is slid along the vector by a defined number of elements. The window is used to select a second set of elements in the vector, wherein the first set of elements and the second set of elements share at least one common element. A second element is selected from the second set of elements having the highest absolute value.