3 papers
cs.CV2026
Generative Augmentation for EEG Motor Imagery Classification: A Class-Conditional VAE with Cycle-Consistent Decoder Refinement
Matei Moldoveanu, Alain Sirois, Claire Ben Ali +2
We investigate whether a generative model can supply useful synthetic motor-imagery (MI) electroencephalography (EEG) trials that improve the accuracy of independent downstream cla…
cs.LG2021
In-Network Learning: Distributed Training and Inference in Networks
Matei Moldoveanu, Abdellatif Zaidi
It is widely perceived that leveraging the success of modern machine learning techniques to mobile devices and wireless networks has the potential of enabling important new service…
stat.ML2021
On In-network learning. A Comparative Study with Federated and Split Learning
Matei Moldoveanu, Abdellatif Zaidi
In this paper, we consider a problem in which distributively extracted features are used for performing inference in wireless networks. We elaborate on our proposed architecture, w…