no code implementations • CVPR 2021 • Dan Amir, Yair Weiss
Perceptual metrics based on features of deep Convolutional Neural Networks (CNNs) have shown remarkable success when used as loss functions in a range of computer vision problems and significantly outperform classical losses such as L1 or L2 in pixel space.
no code implementations • 9 Dec 2018 • Daphna Weinshall, Dan Amir
We also prove that when the ideal difficulty score is fixed, the convergence rate is monotonically increasing with respect to the loss of the current hypothesis at each point.
no code implementations • ICML 2018 • Daphna Weinshall, Gad Cohen, Dan Amir
We provide theoretical investigation of curriculum learning in the context of stochastic gradient descent when optimizing the convex linear regression loss.