DARPA: Hyper-Dimensional Data Enabled Neural Networks (HyDDENN

קרןUS Department of Defense
סוגResearch Grants
תאריך אחרון11/12/2019
פקולטהEngineering, Exact Sciences


The HyDDENN program seeks new data enabled neural network (NN) architectures to break the reliance on large MAC-based DNNs. The goal of HyDDENN is to significantly reduce AI hardware complexity by reducing parameter count by at least 10x, while maintaining SOA accuracy in comparison with a similar MAC-based DNN solution.

Phase 1: Feasibility Study (base)

Phase 2: Proof of Concept (option)



Funding: Phase 1- $300,000 Phase 2- $700,000
Duration: 18 months (Phase 1: 6 months; Phase 2: 12 months)
Researh Authority due date: 4.12.19
קבצים מצורפים
עדכון אחרוןעדכון אחרון: 18/11/2019
אוניברסיטת תל-אביב, ת.ד. 39040, תל-אביב 6997801
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