11 citations · 27 across the 5 of their papers we have counts for
7 papers
Can Calibration Improve Sample Prioritization?
Ganesh Tata, Gautham Krishna Gudur, Gopinath Chennupati +1
Calibration can reduce overconfident predictions of deep neural networks, but can calibration also accelerate training? In this paper, we show that it can when used to prioritize s…
Zero-Shot Federated Learning with New Classes for Audio Classification
Gautham Krishna Gudur, Satheesh K. Perepu
Federated learning is an effective way of extracting insights from different user devices while preserving the privacy of users. However, new classes with completely unseen data di…
Bayesian Active Learning for Wearable Stress and Affect Detection
Abhijith Ragav, Gautham Krishna Gudur
In the recent past, psychological stress has been increasingly observed in humans, and early detection is crucial to prevent health risks. Stress detection using on-device deep lea…
Federated Learning with Heterogeneous Labels and Models for Mobile Activity Monitoring
Gautham Krishna Gudur, Satheesh K. Perepu
Various health-care applications such as assisted living, fall detection, etc., require modeling of user behavior through Human Activity Recognition (HAR). Such applications demand…
Resource-Constrained Federated Learning with Heterogeneous Labels and Models
Gautham Krishna Gudur, Bala Shyamala Balaji, Satheesh K. Perepu
Various IoT applications demand resource-constrained machine learning mechanisms for different applications such as pervasive healthcare, activity monitoring, speech recognition, r…
ActiveHARNet: Towards On-Device Deep Bayesian Active Learning for Human Activity Recognition
Gautham Krishna Gudur, Prahalathan Sundaramoorthy, Venkatesh Umaashankar
Various health-care applications such as assisted living, fall detection etc., require modeling of user behavior through Human Activity Recognition (HAR). HAR using mobile- and wea…