12 July - 25 July 2019

1814 new papers

Etymo Newsletter provides the latest development in machine learning research, including the most popular datasets and the most trending papers in the past two weeks.

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Fortnight Summary

Popular datasets include MNIST, ImageNet, CIFAR-10, KITTI, COCO, and Cityscapes. Our trending phrases are Answer Set, for which we have five articles, Perception Bias, and Sound Events. In our trending papers section, we include a paper on the analogy between neural networks and the learning and development in human brains, a new SGD optimizer called Lookahead, and a new image dataset to significantly improve the accuracy and robustness of classifiers.

Popular Datasets

Here are most mentioned datasets over the last two weeks.

Name Type Number of Papers
MNIST Handwritten Digits 58
ImageNet Image Dataset 46
CIFAR-10 Tiny Image Dataset in 10 Classes 28
KITTI Autonomous Driving 26
COCO Common Objects in Context 20
Cityscapes Images from 50 different cities 17

Trending Phrases

In this section, we present a list of phrases that appeared significantly more in this newsletter than the previous newsletters.

Etymo Trending

Presented below is a list of the most trending papers added in the last two weeks.

  • What does it mean to understand a neural network?:
    The authors give an analogy comparing neural networks to the development and learning in brains.

  • Lookahead Optimizer: k steps forward, 1 step back:
    Lookahead optimizer is a new optimization algorithm of stochastic gradient descent (SGD). Lookahead is orthogonal to a) adaptive learning rate schemes, such as AdaGrad and Adam, and b) accelerated schemes, such as heavy-ball and Nesterov momentum. The new Lookahead algorithm iteratively updates two sets of weights.

  • Natural Adversarial Examples:
    This is a new dataset to measure classifier robustness. This dataset contains 7,500 curated natural adversarial examples, which are real-world, unmodified, and naturally occurring examples.

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