Use Active Learning to Improve SGD [Better title?]

Inspired by active learning, we propose two alternatives to re-weight training samples based on lightweight estimates of sample uncertainty in stochastic gradient descent (SGD). Extensive experimental results on six datasets show that our methods reliably improve accuracy in various network architectures, including additional gains on top of other popular training techniques (Paper, Poster).