no code implementations • 9 May 2021 • Deeksha Dangwal, Vincent T. Lee, Hyo Jin Kim, Tianwei Shen, Meghan Cowan, Rajvi Shah, Caroline Trippel, Brandon Reagen, Timothy Sherwood, Vasileios Balntas, Armin Alaghi, Eddy Ilg
This poses a potential risk to user privacy.
no code implementations • 15 Feb 2021 • Berivan Isik, Kristy Choi, Xin Zheng, Tsachy Weissman, Stefano Ermon, H. -S. Philip Wong, Armin Alaghi
Compression and efficient storage of neural network (NN) parameters is critical for applications that run on resource-constrained devices.
no code implementations • NeurIPS Workshop DL-IG 2020 • Berivan Isik, Kristy Choi, Xin Zheng, H.-S. Philip Wong, Stefano Ermon, Tsachy Weissman, Armin Alaghi
Efficient compression and storage of neural network (NN) parameters is critical for resource-constrained, downstream machine learning applications.
2 code implementations • 15 Feb 2019 • Vincent T. Lee, Samuel Archibald Elliot, Armin Alaghi, Luis Ceze
Stochastic computing (SC) is a high density, low-power computation technique which encodes values as unary bitstreams instead of binary-encoded (BE) values.
1 code implementation • 10 Oct 2018 • Vincent T. Lee, Armin Alaghi, Luis Ceze, Mark Oskin
Stochastic computing (SC) is an emerging computing technique which offers higher computational density, and lower power over binary-encoded (BE) computation.
no code implementations • 14 Jun 2017 • Sung Kim, Patrick Howe, Thierry Moreau, Armin Alaghi, Luis Ceze, Visvesh Sathe
As a result of the increasing demand for deep neural network (DNN)-based services, efforts to develop dedicated hardware accelerators for DNNs are growing rapidly.