12 citations · 21 across the 7 of their papers we have counts for
9 papers
Interpretability of Fine-grained Classification of Sadness and Depression
Tiasa Singha Roy, Priyam Basu, Aman Priyanshu +1
While sadness is a human emotion that people experience at certain times throughout their lives, inflicting them with emotional disappointment and pain, depression is a longer term…
Privacy enabled Financial Text Classification using Differential Privacy and Federated Learning
Priyam Basu, Tiasa Singha Roy, Rakshit Naidu +1
Privacy is important considering the financial Domain as such data is highly confidential and sensitive. Natural Language Processing (NLP) techniques can be applied for text classi…
Efficient Hyperparameter Optimization for Differentially Private Deep Learning
Aman Priyanshu, Rakshit Naidu, Fatemehsadat Mireshghallah +1
Tuning the hyperparameters in the differentially private stochastic gradient descent (DPSGD) is a fundamental challenge. Unlike the typical SGD, private datasets cannot be used man…
Towards Quantifying the Carbon Emissions of Differentially Private Machine Learning
Rakshit Naidu, Harshita Diddee, Ajinkya Mulay +3
In recent years, machine learning techniques utilizing large-scale datasets have achieved remarkable performance. Differential privacy, by means of adding noise, provides strong pr…
When Differential Privacy Meets Interpretability: A Case Study
Rakshit Naidu, Aman Priyanshu, Aadith Kumar +3
Given the increase in the use of personal data for training Deep Neural Networks (DNNs) in tasks such as medical imaging and diagnosis, differentially private training of DNNs is s…
FedPandemic: A Cross-Device Federated Learning Approach Towards Elementary Prognosis of Diseases During a Pandemic
Aman Priyanshu, Rakshit Naidu
The amount of data, manpower and capital required to understand, evaluate and agree on a group of symptoms for the elementary prognosis of pandemic diseases is enormous. In this pa…