Next meetup scheduled: Efficient Pruning for Machine Learning under Homomorphic Encryption
on January 4th, 4pm CEST (Paris, FR)
Greetings cryptographers!
🗓️ The next FHE.org meetup is scheduled for Thursday, January 4th at 4pm CEST (Paris, FR).
The meetup features Dr. Subhankar Pal, a research scientist at IBM T.J. Watson Research Center, presenting Efficient Pruning for Machine Learning under Homomorphic Encryption.
Here is the link to register:
Abstract
Homomorphic encryption (HE) based privacy-preserving machine learning (PPML) solutions are gaining widespread popularity. However, model sizes in PPML are limited by computational speed and memory requirements for inference. Pruning the model parameters improves latency and memory in plaintext ML, but has little impact if directly applied to HE-based PPML. This presentation introduces a framework called HE-PEx that carefully applies parameter pruning and permutation methods, on top of a packing technique called tile tensors, for reducing the latency and memory of PPML inference.
About the speakers
Dr. Subhankar Pal is a research scientist at IBM T.J. Watson Research Center in Yorktown Heights, USA. He currently works on hardware and software co-designed approaches for accelerating homomorphic encryption, and SoC-level design methodologies. In the past, he has worked on reconfigurable computer architectures, machine learning hardware and compiler techniques, resource scheduling, among others.
Resources from last meetup
We’re happy to have had Jean-Philippe Bossuat last month presenting on Lattigo v5: Deep Dive.
You can access those resources on the FHE.org website here.
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See you soon!
The FHE.org team