406 citations · 527 across the 20 of their papers we have counts for
5 papers · 1 filter
A-LAQ: Adaptive Lazily Aggregated Quantized Gradient
Afsaneh Mahmoudi, José Mairton Barros Da Silva Júnior, Hossein S. Ghadikolaei +1
Federated Learning (FL) plays a prominent role in solving machine learning problems with data distributed across clients. In FL, to reduce the communication overhead of data betwee…
FedCau: A Proactive Stop Policy for Communication and Computation Efficient Federated Learning
Afsaneh Mahmoudi, Hossein S. Ghadikolaei, José Mairton Barros Da Silva Júnior +1
This paper investigates efficient distributed training of a Federated Learning~(FL) model over a wireless network of wireless devices. The communication iterations of the distribut…
Communication-efficient Variance-reduced Stochastic Gradient Descent
Hossein S. Ghadikolaei, Sindri Magnusson
We consider the problem of communication efficient distributed optimization where multiple nodes exchange important algorithm information in every iteration to solve large problems…
Learning Kolmogorov Models for Binary Random Variables
Hadi Ghauch, Mikael Skoglund, Hossein Shokri-Ghadikolaei +2
We summarize our recent findings, where we proposed a framework for learning a Kolmogorov model, for a collection of binary random variables. More specifically, we derive condition…
A Unified Framework for Training Neural Networks
Hadi Ghauch, Hossein Shokri-Ghadikolaei, Carlo Fischione +1
The lack of mathematical tractability of Deep Neural Networks (DNNs) has hindered progress towards having a unified convergence analysis of training algorithms, in the general sett…