6 accepted papers
Model pruning has gained traction as a promising defense strategy against backdoor attacks in deep learning. However, existing pruning-based approaches often fall short in accurately identifying and removing the specific parameters responsible for inducing backdoor behaviors. Despite the dominance o…
We investigate the robustness of the recently introduced partialsharing online federated learning (PSO-Fed) algorithm against model-poisoning attacks. To this end, we analyze the performance of the PSO-Fed algorithm in the presence of Byzantine clients, who may clandestinely corrupt their local mode…
Regulatory compliance auditing in agrifood processing facilities is crucial for upholding the highest standards of quality assurance and traceability. However, the current manual and intermittent approaches to auditing present significant challenges and risks, potentially leading to gaps or loophole…
We propose a new distributed algorithm to solve the total least-squares (TLS) problem when data are distributed over a multi-agent network. To develop the proposed algorithm, named distributed ADMM TLS (DA-TLS), we reformulate the TLS problem as a parametric semidefinite program and solve it using t…
We consider fusing an arbitrary number of multiband, i.e., panchromatic, multispectral, or hyperspectral, images of the same scene. Using the well-known forward observation and linear mixture models, a vector total-variation penalty, and appropriate constraints, we cast this problem as a convex opti…
We develop a fully-distributed iterative algorithm for finding a model-distributed least-squares solution of systems of linear equations over sensor networks. Here, model-distributed means the solution vector is distributed across the network rather than being replicated at each node. For this purpo…