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Communications of the ACM

Research Archive


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The Research archive provides access to all Research articles published in past issues of Communications of the ACM.

June 2017


From Communications of the ACM

Technical Perspective: What Led Computer Vision to Deep Learning?

We are in the middle of the third wave of interest in artificial neural networks as the leading paradigm for machine learning. "ImageNet Classification with Deep Convolutional Neural Networks" is the paper most responsible for…


From Communications of the ACM

ImageNet Classification with Deep Convolutional Neural Networks

ImageNet Classification with Deep Convolutional Neural Networks

In the 1980s backpropagation did not live up to the very high expectations of its advocates. Twenty years later, we know what went wrong: for deep neural networks to shine, they need far more labeled data and hugely more computation…


From Communications of the ACM

Unexpected Power of Low-Depth Arithmetic Circuits

Unexpected Power of Low-Depth Arithmetic Circuits

Several earlier results have shown that it is possible to rearrange basic computational elements in surprising ways to give more efficient algorithms. The main result of this article is along a similar vein.


From Communications of the ACM

Technical Perspective: Low-depth Arithmetic Circuits

The past few years have seen a revolution in our understanding of arithmetic circuits. "Unexpected Power of Low-Depth Arithmetic Circuits" by Gupta et al. on the "chasm at depth 3" is one of the culminations of this new understanding…