Search Results for author: Arun Iyengar

Found 4 papers, 2 papers with code

Gradient-Leakage Resilient Federated Learning

1 code implementation2 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.

Federated Learning

Patient-Specific Seizure Prediction Using Single Seizure Electroencephalography Recording

no code implementations14 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.

EEG Seizure prediction

Demystifying Learning Rate Policies for High Accuracy Training of Deep Neural Networks

1 code implementation18 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).

Image Classification

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