3 papers
cs.LG2026
On Imbalanced Regression with Hoeffding Trees
Pantia-Marina Alchirch, Dimitrios I. Diochnos
Many real-world applications generate continuous data streams for regression. Hoeffding trees and their variants have a long-standing tradition due to their effectiveness, either a…
cs.CV2025
Meta Co-Training: Two Views are Better than One
Jay C. Rothenberger, Dimitrios I. Diochnos
In many critical computer vision scenarios unlabeled data is plentiful, but labels are scarce and difficult to obtain. As a result, semi-supervised learning which leverages unlabel…
cs.CV2025
A Review of Pseudo-Labeling for Computer Vision
Patrick Kage, Jay C. Rothenberger, Pavlos Andreadis +1
Deep neural models have achieved state of the art performance on a wide range of problems in computer science, especially in computer vision. However, deep neural networks often re…