Fast Algorithms for Convolutional Neural Networks
Deep convolutional neural networks take GPU days of compute time to train on large data sets. Pedestrian detection for self driving cars requires very low latency. Image recognition for mobile phones is constrained by limited processing resources. The success of convolutional neural networks in these situations is limited by how fast we can compute them. Conventional FFT based convolution is fast
PIN number analysis
A good friend of mine, Ian, recently forwarded me an internet joke. The headline was something like: “All credit card PIN numbers in the World leaked” The body of the message simply said 0000 0001 0002 0003 0004 … Ian’s messages made me chuckle. Then, later the same day, I read this XKCD cartoon. The merging of these two humorous topics created the seed for this article. I love Randall’s work. My
Statisticians Found One Thing They Can Agree On: It’s Time To Stop Misusing P-Values
This is an archived site and is no longer being updated. New 538 articles can be found at www.abcnews.com/538. Little p-value What are you trying to say Of significance? — Stephen Ziliak, Roosevelt University economics professor How many statisticians does it take to ensure at least a 50 percent chance of a disagreement about p-values? According to a tongue-in-cheek assessment by statistician Geor
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Moving from Solutions to Problems | Folding Burritos
google/codesearch: Fast, indexed regexp search over large file trees