3 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 3 cited
Accelerating Batch Active Learning Using Continual Learning Techniques
Arnav Das, Gantavya Bhatt, Megh Bhalerao +3
A major problem with Active Learning (AL) is high training costs since models are typically retrained from scratch after every query round. We start by demonstrating that standard…
cs.LG2021★ 2 cited
Ex uno plures: Splitting One Model into an Ensemble of Subnetworks
Zhilu Zhang, Vianne R. Gao, Mert R. Sabuncu
Monte Carlo (MC) dropout is a simple and efficient ensembling method that can improve the accuracy and confidence calibration of high-capacity deep neural network models. However,…