[HTML][HTML] Survey of decentralized solutions with mobile devices for user location tracking, proximity detection, and contact tracing in the COVID-19 era
Some of the recent developments in data science for worldwide disease control have
involved research of large-scale feasibility and usefulness of digital contact tracing, user …
involved research of large-scale feasibility and usefulness of digital contact tracing, user …
A Nesterov-like gradient tracking algorithm for distributed optimization over directed networks
In this article, we concentrate on dealing with the distributed optimization problem over a
directed network, where each unit possesses its own convex cost function and the principal …
directed network, where each unit possesses its own convex cost function and the principal …
Secure decentralized image classification with multiparty homomorphic encryption
Decentralized image classification plays a key role in various scenarios due to its attractive
properties, including tolerating high network latency and less prone to single-point failures …
properties, including tolerating high network latency and less prone to single-point failures …
Encrypted cooperative control revisited
AB Alexandru, MS Darup… - 2019 IEEE 58th …, 2019 - ieeexplore.ieee.org
Distributed systems are ubiquitous in present-day technologies like smart cities. Such
applications require decentralized control, which reduces the load on a single central party …
applications require decentralized control, which reduces the load on a single central party …
On the (in) security of peer-to-peer decentralized machine learning
D Pasquini, M Raynal… - 2023 IEEE Symposium on …, 2023 - ieeexplore.ieee.org
In this work, we carry out the first, in-depth, privacy analysis of Decentralized Learning—a
collaborative machine learning framework aimed at addressing the main limitations of …
collaborative machine learning framework aimed at addressing the main limitations of …
On the privacy of decentralized machine learning
D Pasquini, M Raynal, C Troncoso - 2022 - infoscience.epfl.ch
In this work, we carry out the first, in-depth, privacy analysis of Decentralized Learning--a
collaborative machine learning framework aimed at circumventing the main limitations of …
collaborative machine learning framework aimed at circumventing the main limitations of …
Convergence and privacy of decentralized nonconvex optimization with gradient clipping and communication compression
Achieving communication efficiency in decentralized machine learning has been attracting
significant attention, with communication compression recognized as an effective technique …
significant attention, with communication compression recognized as an effective technique …
Decentralized and Private Solution for the Optimal Dispatch of Integrated Wind Farms with Shared Energy Storage Systems
The integration of variable wind power faces additional challenges with the increasing
global emphasis on renewable energy integration. Energy storage systems (ESS) can offer …
global emphasis on renewable energy integration. Energy storage systems (ESS) can offer …
Privacy-preserving incremental ADMM for decentralized consensus optimization
The alternating direction method of multipliers (ADMM) has been recently recognized as a
promising optimizer for large-scale machine learning models. However, there are very few …
promising optimizer for large-scale machine learning models. However, there are very few …
Privacy-preserving decentralized deep learning with multiparty homomorphic encryption
Decentralized deep learning plays a key role in collaborative model training due to its
attractive properties, including tolerating high network latency and less prone to single-point …
attractive properties, including tolerating high network latency and less prone to single-point …