no code implementations • 1 Mar 2024 • Adrian Shuai Li, Arun Iyengar, Ashish Kundu, Elisa Bertino
The latter data may follow a distinct distribution.
1 code implementation • 2 Jul 2021 • Wenqi Wei, Ling Liu, Yanzhao Wu, Gong Su, Arun Iyengar
This paper presents a gradient leakage resilient approach to privacy-preserving federated learning with per training example-based client differential privacy, coined as Fed-CDP.
no code implementations • 14 Nov 2020 • Zaid Bin Tariq, Arun Iyengar, Lara Marcuse, Hui Su, Bülent Yener
But these models require a considerable number of patient-specific seizures to be recorded for extracting the preictal and interictal EEG data for training a classifier.
no code implementations • 21 Nov 2019 • Mustafa Canim, Cristina Cornelio, Arun Iyengar, Ryan Musa, Mariano Rodrigez Muro
Unstructured enterprise data such as reports, manuals and guidelines often contain tables.
1 code implementation • 18 Aug 2019 • Yanzhao Wu, Ling Liu, Juhyun Bae, Ka-Ho Chow, Arun Iyengar, Calton Pu, Wenqi Wei, Lei Yu, Qi Zhang
Learning Rate (LR) is an important hyper-parameter to tune for effective training of deep neural networks (DNNs).