150 citations · 488 across the 33 of their papers we have counts for
3 papers · 1 filter
The Dynamic of Consensus in Deep Networks and the Identification of Noisy Labels
Daniel Shwartz, Uri Stern, Daphna Weinshall
Deep neural networks have incredible capacity and expressibility, and can seemingly memorize any training set. This introduces a problem when training in the presence of noisy labe…
Active Learning Through a Covering Lens
Ofer Yehuda, Avihu Dekel, Guy Hacohen +1
Deep active learning aims to reduce the annotation cost for the training of deep models, which is notoriously data-hungry. Until recently, deep active learning methods were ineffec…
Active Learning on a Budget: Opposite Strategies Suit High and Low Budgets
Guy Hacohen, Avihu Dekel, Daphna Weinshall
Investigating active learning, we focus on the relation between the number of labeled examples (budget size), and suitable querying strategies. Our theoretical analysis shows a beh…