150 citations · 488 across the 33 of their papers we have counts for
Showing 2018Show all
3 papers · 1 filter
cs.LG2018★ 5 cited
Theory of Curriculum Learning, with Convex Loss Functions
Daphna Weinshall, Dan Amir
Curriculum Learning - the idea of teaching by gradually exposing the learner to examples in a meaningful order, from easy to hard, has been investigated in the context of machine l…
cs.LG2018★ 40 cited
Gaussian Mixture Generative Adversarial Networks for Diverse Datasets, and the Unsupervised Clustering of Images
Matan Ben-Yosef, Daphna Weinshall
Generative Adversarial Networks (GANs) have been shown to produce realistically looking synthetic images with remarkable success, yet their performance seems less impressive when t…
cs.LG2018★ 150 cited
Curriculum Learning by Transfer Learning: Theory and Experiments with Deep Networks
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. We prove that the rate…