HE-PEx: Efficient Machine Learning under Homomorphic Encryption using Pruning, Permutation and Expansion

no code implementations • 7 Jul 2022 • Ehud Aharoni, Moran Baruch, Pradip Bose, Alper Buyuktosunoglu, Nir Drucker, Subhankar Pal, Tomer Pelleg, Kanthi Sarpatwar, Hayim Shaul, Omri Soceanu, Roman Vaculin

In this work, we propose a novel set of pruning methods that reduce the latency and memory requirement, thus bringing the effectiveness of plaintext pruning methods to HE.

BIG-bench Machine Learning Privacy Preserving

Improving Efficiency in Large-Scale Decentralized Distributed Training

no code implementations • 4 Feb 2020 • Wei Zhang, Xiaodong Cui, Abdullah Kayi, Mingrui Liu, Ulrich Finkler, Brian Kingsbury, George Saon, Youssef Mroueh, Alper Buyuktosunoglu, Payel Das, David Kung, Michael Picheny

Decentralized Parallel SGD (D-PSGD) and its asynchronous variant Asynchronous Parallel SGD (AD-PSGD) is a family of distributed learning algorithms that have been demonstrated to perform well for large-scale deep learning tasks.

speech-recognition Speech Recognition

A Highly Efficient Distributed Deep Learning System For Automatic Speech Recognition

no code implementations • 10 Jul 2019 • Wei Zhang, Xiaodong Cui, Ulrich Finkler, George Saon, Abdullah Kayi, Alper Buyuktosunoglu, Brian Kingsbury, David Kung, Michael Picheny

On commonly used public SWB-300 and SWB-2000 ASR datasets, ADPSGD can converge with a batch size 3X as large as the one used in SSGD, thus enable training at a much larger scale.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1