114 citations · 126 across the 9 of their papers we have counts for
2 papers
cs.CL2016★ 11 cited
Named Entity Recognition for Novel Types by Transfer Learning
Lizhen Qu, Gabriela Ferraro, Liyuan Zhou +2
In named entity recognition, we often don't have a large in-domain training corpus or a knowledge base with adequate coverage to train a model directly. In this paper, we propose a…
stat.ML2016★ 114 cited
Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach
Giorgio Patrini, Alessandro Rozza, Aditya Menon +2
We present a theoretically grounded approach to train deep neural networks, including recurrent networks, subject to class-dependent label noise. We propose two procedures for loss…