2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Active Learning with a Noisy Annotator
Netta Shafir, Guy Hacohen, Daphna Weinshall
Active Learning (AL) aims to reduce annotation costs by strategically selecting the most informative samples for labeling. However, most active learning methods struggle in the low…
cs.LG2023★ 2 cited
Pruning the Unlabeled Data to Improve Semi-Supervised Learning
Guy Hacohen, Daphna Weinshall
In the domain of semi-supervised learning (SSL), the conventional approach involves training a learner with a limited amount of labeled data alongside a substantial volume of unlab…
cs.CV2023
Semi-Supervised Learning in the Few-Shot Zero-Shot Scenario
Noam Fluss, Guy Hacohen, Daphna Weinshall
Semi-Supervised Learning (SSL) is a framework that utilizes both labeled and unlabeled data to enhance model performance. Conventional SSL methods operate under the assumption that…