Hard Mixtures of Experts for Large Scale Weakly Supervised Vision

Training convolutional networks (CNN's) that fit on a single GPU with minibatch stochastic gradient descent has become effective in practice. However, there is still no effective method for training large CNN's that do not fit in the memory of a few GPU cards, or for parallelizing CNN training. In this work we show that a simple hard mixture of experts model can be efficiently trained to good effect on large scale hashtag (multilabel) prediction tasks. Mixture of experts models are not new (Jacobs et. al. 1991, Collobert et. al. 2003), but in the past, researchers have had to devise sophisticated methods to deal with data fragmentation. We show empirically that modern weakly supervised data sets are large enough to support naive partitioning schemes where each data point is assigned to a single expert. Because the experts are independent, training them in parallel is easy, and evaluation is cheap for the size of the model. Furthermore, we show that we can use a single decoding layer for all the experts, allowing a unified feature embedding space. We demonstrate that it is feasible (and in fact relatively painless) to train far larger models than could be practically trained with standard CNN architectures, and that the extra capacity can be well used on current datasets.Comment: Appearing in CVPR 201

Sexual Assault: The Crisis That Blindsided Higher Education

This paper begins by examining the history of university oversight of sexual assault cases and why sexual assault has become such a problem on college and university campuses. Next the paper will examine existing laws that govern how colleges handle sexual assault cases. Subsequently, this article will discuss the loopholes in existing laws that have allowed institutions of higher learning to not only ignore the problem of sexual assault, but also underreport incidents of sexual assault. Current proposed legislation and administrative actions will be explored that attempt to close these loopholes forcing universities to answer for their failure to handle sexual assault cases properly and revamp their existing policies to better protect victims of sexual assault. Finally, the authors provide potential solutions for what is likely the next big crisis in higher education