4 papers
Federated Learning of Binary Neural Networks: Enabling Low-Cost Inference
Nitin Priyadarshini Shankar, Soham Lahiri, Sheetal Kalyani +1
Federated Learning (FL) preserves privacy by distributing training across devices. However, using DNNs is computationally intensive at the low-powered edge during inference. Edge d…
BERTO: Intent-Driven Network Time Series Forecasting via Natural Language Operator Preferences
Nitin Priyadarshini Shankar, Vaibhav Singh, Sheetal Kalyani +1
Traditional cellular traffic forecasting models are optimized for minimizing symmetric errors, leaving them indifferent to shifting operational priorities. To bridge this gap, we i…
Golden Ratio Search: A Low-Power Adversarial Attack for Deep Learning based Modulation Classification
Deepsayan Sadhukhan, Nitin Priyadarshini Shankar, Sheetal Kalyani
We propose a minimal power white box adversarial attack for Deep Learning based Automatic Modulation Classification (AMC). The proposed attack uses the Golden Ratio Search (GRS) me…
Binarized ResNet: Enabling Robust Automatic Modulation Classification at the resource-constrained Edge
Deepsayan Sadhukhan, Nitin Priyadarshini Shankar, Nancy Nayak +2
Recently, deep neural networks (DNNs) have been used extensively for automatic modulation classification (AMC), and the results have been quite promising. However, DNNs have high m…