1 citations · 1 across the 3 of their papers we have counts for
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Adaptive Threshold-Driven Continuous Greedy Method for Scalable Submodular Optimization
Mohammadreza Rostami, Solmaz S. Kia
Submodular maximization under matroid constraints is a fundamental problem in combinatorial optimization with applications in sensing, data summarization, active learning, and reso…
FedScalar: Federated Learning with Scalar Communication for Bandwidth-Constrained Networks
M. Rostami, S. S. Kia
In bandwidth-constrained federated learning~(FL) settings, the repeated upload of high-dimensional model updates from agents to a central server constitutes the primary bottleneck,…
FedMPDD: Communication-Efficient Federated Learning with Privacy Preservation Attributes via Projected Directional Derivative
Mohammadreza Rostami, Solmaz S. Kia
This paper introduces \texttt{FedMPDD} (\textbf{Fed}erated Learning via \textbf{M}ulti-\textbf{P}rojected \textbf{D}irectional \textbf{D}erivatives), a novel algorithm that simulta…
Projected Forward Gradient-Guided Frank-Wolfe Algorithm via Variance Reduction
M. Rostami, S. S. Kia
This paper aims to enhance the use of the Frank-Wolfe (FW) algorithm for training deep neural networks. Similar to any gradient-based optimization algorithm, FW suffers from high c…