collaborators

5 papers

eess.SP2022

Turning Silver into Gold: Domain Adaptation with Noisy Labels for Wearable Cardio-Respiratory Fitness Prediction

Yu Wu, Dimitris Spathis, Hong Jia +5

Deep learning models have shown great promise in various healthcare applications. However, most models are developed and validated on small-scale datasets, as collecting high-quali…

cs.LG2022

Improving Feature Generalizability with Multitask Learning in Class Incremental Learning

Dong Ma, Chi Ian Tang, Cecilia Mascolo

Many deep learning applications, like keyword spotting, require the incorporation of new concepts (classes) over time, referred to as Class Incremental Learning (CIL). The major ch…

cs.LG2022

YONO: Modeling Multiple Heterogeneous Neural Networks on Microcontrollers

Young D. Kwon, Jagmohan Chauhan, Cecilia Mascolo

With the advancement of Deep Neural Networks (DNN) and large amounts of sensor data from Internet of Things (IoT) systems, the research community has worked to reduce the computati…

cs.LG2022

Enabling On-Device Smartphone GPU based Training: Lessons Learned

Anish Das, Young D. Kwon, Jagmohan Chauhan +1

Deep Learning (DL) has shown impressive performance in many mobile applications. Most existing works have focused on reducing the computational and resource overheads of running De…

cs.SD2022

A Summary of the ComParE COVID-19 Challenges

Harry Coppock, Alican Akman, Christian Bergler +17

The COVID-19 pandemic has caused massive humanitarian and economic damage. Teams of scientists from a broad range of disciplines have searched for methods to help governments and c…