1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 1 cited
Querying Easily Flip-flopped Samples for Deep Active Learning
Seong Jin Cho, Gwangsu Kim, Junghyun Lee +2
Active learning is a machine learning paradigm that aims to improve the performance of a model by strategically selecting and querying unlabeled data. One effective selection strat…
cs.LG2023
ESD: Expected Squared Difference as a Tuning-Free Trainable Calibration Measure
Hee Suk Yoon, Joshua Tian Jin Tee, Eunseop Yoon +4
Studies have shown that modern neural networks tend to be poorly calibrated due to over-confident predictions. Traditionally, post-processing methods have been used to calibrate th…