3 code implementations • 20 Feb 2024 • Jonathan Dan, Una Pale, Alireza Amirshahi, William Cappelletti, Thorir Mar Ingolfsson, Xiaying Wang, Andrea Cossettini, Adriano Bernini, Luca Benini, Sándor Beniczky, David Atienza, Philippe Ryvlin
Based on existing guidelines and recommendations, the framework introduces a set of recommendations and standards related to datasets, file formats, EEG data input content, seizure annotation input and output, cross-validation strategies, and performance metrics.
1 code implementation • 20 Dec 2023 • Alireza Amirshahi, Giovanni Ansaloni, David Atienza
Additionally, we address the overhead of non-GEMM operations in transformer models within the scope of this memory data arrangement.
no code implementations • 28 Mar 2023 • Jingwei Sun, Zhixu Du, Anna Dai, Saleh Baghersalimi, Alireza Amirshahi, David Atienza, Yiran Chen
In this paper, we propose \textbf{Party-wise Dropout} to improve the VFL model's robustness against the unexpected exit of passive parties and a defense method called \textbf{DIMIP} to protect the active party's IP in the deployment phase.
no code implementations • arXiv:1905.02954 2019 • Alireza Amirshahi, Matin Hashemi
This paper presents a novel ECG classification algorithm for real-time cardiac monitoring on ultra low-power wearable devices.