15 citations · 16 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 1 cited
In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer
Yuzhou Cao, Hussein Mozannar, Lei Feng +2
Enabling machine learning classifiers to defer their decision to a downstream expert when the expert is more accurate will ensure improved safety and performance. This objective ca…
cs.LG2023
A Generalized Unbiased Risk Estimator for Learning with Augmented Classes
Senlin Shu, Shuo He, Haobo Wang +3
In contrast to the standard learning paradigm where all classes can be observed in training data, learning with augmented classes (LAC) tackles the problem where augmented classes…
cs.LG2022★ 15 cited
Open-Sampling: Exploring Out-of-Distribution data for Re-balancing Long-tailed datasets
Hongxin Wei, Lue Tao, Renchunzi Xie +2
Deep neural networks usually perform poorly when the training dataset suffers from extreme class imbalance. Recent studies found that directly training with out-of-distribution dat…