36 citations · 111 across the 13 of their papers we have counts for
5 papers · 1 filter
ScionFL: Efficient and Robust Secure Quantized Aggregation
Yaniv Ben-Itzhak, Helen Möllering, Benny Pinkas +7
Secure aggregation is commonly used in federated learning (FL) to alleviate privacy concerns related to the central aggregator seeing all parameter updates in the clear. Unfortunat…
IIsy: Practical In-Network Classification
Changgang Zheng, Zhaoqi Xiong, Thanh T Bui +6
The rat race between user-generated data and data-processing systems is currently won by data. The increased use of machine learning leads to further increase in processing require…
Automating In-Network Machine Learning
Changgang Zheng, Mingyuan Zang, Xinpeng Hong +4
Using programmable network devices to aid in-network machine learning has been the focus of significant research. However, most of the research was of a limited scope, providing a…
QUIC-FL: Quick Unbiased Compression for Federated Learning
Ran Ben Basat, Shay Vargaftik, Amit Portnoy +3
Distributed Mean Estimation (DME), in which clients communicate vectors to a parameter server that estimates their average, is a fundamental building block in communication-eff…
CloudCast: Characterizing Public Clouds Connectivity
Noga H. Rotman, Yaniv Ben-Itzhak, Aran Bergman +4
Public clouds are one of the most thriving technologies of the past decade. Major applications over public clouds require world-wide distribution and large amounts of data exchange…