1 citations · 1 across the 5 of their papers we have counts for
4 papers · 1 filter
Federated Learning with Uncertainty and Personalization via Efficient Second-order Optimization
Shivam Pal, Aishwarya Gupta, Saqib Sarwar +1
Federated Learning (FL) has emerged as a promising method to collaboratively learn from decentralized and heterogeneous data available at different clients without the requirement…
Robust Black-box Testing of Deep Neural Networks using Co-Domain Coverage
Aishwarya Gupta, Indranil Saha, Piyush Rai
Rigorous testing of machine learning models is necessary for trustworthy deployments. We present a novel black-box approach for generating test-suites for robust testing of deep ne…
Insuring Smiles: Predicting routine dental coverage using Spark ML
Aishwarya Gupta, Rahul S. Bhogale, Priyanka Thota +2
Finding suitable health insurance coverage can be challenging for individuals and small enterprises in the USA. The Health Insurance Exchange Public Use Files (Exchange PUFs) datas…
Federated Learning with Uncertainty via Distilled Predictive Distributions
Shrey Bhatt, Aishwarya Gupta, Piyush Rai
Most existing federated learning methods are unable to estimate model/predictive uncertainty since the client models are trained using the standard loss function minimization appro…