no code implementations • 4 Mar 2023 • Yamin Sepehri, Pedram Pad, Ahmet Caner Yüzügüler, Pascal Frossard, L. Andrea Dunbar
In this study, a novel hierarchical training method for deep neural networks is proposed that uses early exits in a divided architecture between edge and cloud workers to reduce the communication cost, training runtime and privacy concerns.
no code implementations • 28 Jun 2021 • Yamin Sepehri, Pedram Pad, Pascal Frossard, L. Andrea Dunbar
Also, in contrast with the previous optical privacy-preserving methods that cannot be trained, our method is data-driven and optimized for the specific application at hand.
no code implementations • CVPR 2020 • Pedram Pad, Simon Narduzzi, Clement Kundig, Engin Turetken, Siavash A. Bigdeli, L. Andrea Dunbar
Despite the substantial progress made in deep learning in recent years, advanced approaches remain computationally intensive.
Ranked #1 on Hand-Gesture Recognition on InAirGestures
no code implementations • ICML 2017 • Pedram Pad, Farnood Salehi, Elisa Celis, Patrick Thiran, Michael Unser
We propose a new statistical dictionary learning algorithm for sparse signals that is based on an $\alpha$-stable innovation model.