150 citations · 488 across the 33 of their papers we have counts for
3 papers · 1 filter
Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation
Uri Stern, Eli Corn, Daphna Weinshall
Overfitting in deep neural networks occurs less frequently than expected. This is a puzzling observation, as theory predicts that greater model capacity should eventually lead to o…
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…
On Local Overfitting and Forgetting in Deep Neural Networks
Uri Stern, Tomer Yaacoby, Daphna Weinshall
The infrequent occurrence of overfitting in deep neural networks is perplexing: contrary to theoretical expectations, increasing model size often enhances performance in practice.…