Deeplite Neutrino (TM): An End-to-End Framework for Constrained Deep Learning Model Optimization

Anush Sankaran, Olivier Mastropietro, Ehsan Saboori, Yasser Idris, Davis Sawyer, Mohammadhossein Askari Hemmat and Ghouthi Boukli Hacene

Paper (2021)

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Department:	Department of Computer Engineering and Software Engineering
ISBN:	9781577358664
PolyPublie URL:	https://publications.polymtl.ca/48695/
Conference Title:	35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence
Conference Date(s):	2021-02-02 - 2021-02-09
Publisher:	Assoc Advancement Artificial Intelligence
DOI:	10.48550/arxiv.2101.04073
Official URL:	https://doi.org/10.48550/arxiv.2101.04073
Date Deposited:	18 Apr 2023 15:00
Last Modified:	21 Mar 2025 16:17

Cite in APA 7:

Sankaran, A., Mastropietro, O., Saboori, E., Idris, Y., Sawyer, D., Askari Hemmat, M., & Hacene, G. B. (2021, February). Deeplite Neutrino (TM): An End-to-End Framework for Constrained Deep Learning Model Optimization [Paper]. 35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence. https://doi.org/10.48550/arxiv.2101.04073

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