3 papers
cs.LG2018
Regularized adversarial examples for model interpretability
Yoel Shoshan, Vadim Ratner
As machine learning algorithms continue to improve, there is an increasing need for explaining why a model produces a certain prediction for a certain input. In recent years, sever…
cs.CV2018
Learning multiple non-mutually-exclusive tasks for improved classification of inherently ordered labels
Vadim Ratner, Yoel Shoshan, Tal Kachman
Medical image classification involves thresholding of labels that represent malignancy risk levels. Usually, a task defines a single threshold, and when developing computer-aided d…
cs.CV2018
AdapterNet - learning input transformation for domain adaptation
Alon Hazan, Yoel Shoshan, Daniel Khapun +2
Deep neural networks have demonstrated impressive performance in various machine learning tasks. However, they are notoriously sensitive to changes in data distribution. Often, eve…