8 citations · 26 across the 7 of their papers we have counts for
7 papers
Accelerating Neural Network Training: A Brief Review
Sahil Nokhwal, Priyanka Chilakalapudi, Preeti Donekal +3
The process of training a deep neural network is characterized by significant time requirements and associated costs. Although researchers have made considerable progress in this a…
Quantum Generative Adversarial Networks: Bridging Classical and Quantum Realms
Sahil Nokhwal, Suman Nokhwal, Saurabh Pahune +1
In this pioneering research paper, we present a groundbreaking exploration into the synergistic fusion of classical and quantum computing paradigms within the realm of Generative A…
Secure Information Embedding in Images with Hybrid Firefly Algorithm
Sahil Nokhwal, Manoj Chandrasekharan, Ankit Chaudhary
Various methods have been proposed to secure access to sensitive information over time, such as the many cryptographic methods in use to facilitate secure communications on the int…
RTRA: Rapid Training of Regularization-based Approaches in Continual Learning
Sahil Nokhwal, Nirman Kumar
Catastrophic forgetting(CF) is a significant challenge in continual learning (CL). In regularization-based approaches to mitigate CF, modifications to important training parameters…
DSS: A Diverse Sample Selection Method to Preserve Knowledge in Class-Incremental Learning
Sahil Nokhwal, Nirman Kumar
Rehearsal-based techniques are commonly used to mitigate catastrophic forgetting (CF) in Incremental learning (IL). The quality of the exemplars selected is important for this purp…
PBES: PCA Based Exemplar Sampling Algorithm for Continual Learning
Sahil Nokhwal, Nirman Kumar
We propose a novel exemplar selection approach based on Principal Component Analysis (PCA) and median sampling, and a neural network training regime in the setting of class-increme…
EmbAu: A Novel Technique to Embed Audio Data Using Shuffled Frog Leaping Algorithm
Sahil Nokhwal, Saurabh Pahune, Ankit Chaudhary
The aim of steganographic algorithms is to identify the appropriate pixel positions in the host or cover image, where bits of sensitive information can be concealed for data encryp…