3 papers
cs.LG2025
Enhancing Efficiency in Multidevice Federated Learning through Data Selection
Fan Mo, Mohammad Malekzadeh, Soumyajit Chatterjee +2
Ubiquitous wearable and mobile devices provide access to a diverse set of data. However, the mobility demand for our devices naturally imposes constraints on their computational an…
cs.LG2025
Deep Unlearn: Benchmarking Machine Unlearning for Image Classification
Xavier F. Cadet, Anastasia Borovykh, Mohammad Malekzadeh +2
Machine unlearning (MU) aims to remove the influence of particular data points from the learnable parameters of a trained machine learning model. This is a crucial capability in li…
cs.LG2024
Vicious Classifiers: Assessing Inference-time Data Reconstruction Risk in Edge Computing
Mohammad Malekzadeh, Deniz Gunduz
Privacy-preserving inference in edge computing paradigms encourages the users of machine-learning services to locally run a model on their private input and only share the models o…