no code implementations • 26 May 2024 • Gabriele Dominici, Pietro Barbiero, Mateo Espinosa Zarlenga, Alberto Termine, Martin Gjoreski, Giuseppe Marra, Marc Langheinrich
Causal opacity denotes the difficulty in understanding the "hidden" causal structure underlying a deep neural network's (DNN) reasoning.
no code implementations • 24 May 2024 • Dario Fenoglio, Gabriele Dominici, Pietro Barbiero, Alberto Tonda, Martin Gjoreski, Marc Langheinrich
Federated Learning (FL), a privacy-aware approach in distributed deep learning environments, enables many clients to collaboratively train a model without sharing sensitive data, thereby reducing privacy risks.
no code implementations • 9 Apr 2024 • Fatima Ezzeddine, Mirna Saad, Omran Ayoub, Davide Andreoletti, Martin Gjoreski, Ihab Sbeity, Marc Langheinrich, Silvia Giordano
Anomaly detection (AD), also referred to as outlier detection, is a statistical process aimed at identifying observations within a dataset that significantly deviate from the expected pattern of the majority of the data.
1 code implementation • 2 Feb 2024 • Gabriele Dominici, Pietro Barbiero, Francesco Giannini, Martin Gjoreski, Giuseppe Marra, Marc Langheinrich
"), and imagine alternative scenarios that could result in different predictions (the "What if?").