Professor Blei is also a bit of a superstar, so that didn’t hurt.
It’s no surprise to see this in the Top 10 either, given the huge appeal of this parallelization technique for breaking down huge computations into easily executable and recombinable chunks.
This is another machine learning paper and its presence in the top 10 is primarily due to AI, with a small contribution from folks listing neural networks as their discipline, most likely due to the paper being published in IEEE Transactions on Neural Networks.
Reinforcement learning is essentially a technique that borrows from biology, where the behavior of an intelligent agent is is controlled by the amount of positive stimuli, or reinforcement, it receives in an environment where there are many different interacting positive and negative stimuli.
This is how we’ll teach the robots behaviors in a human fashion, before they rise up and destroy us.
Popular among AI and information retrieval researchers, this paper discusses recommendation algorithms and classifies them into collaborative, content-based, or hybrid.Here’s what I found: What I found was a fascinating list of topics, with many of the expected fundamental papers like Shannon’s Theory of Information and the Google paper, a strong showing from Mapreduce and machine learning, but also some interesting hints that augmented reality may be becoming more of an actual reality soon.The top graph summarizes the overall results of the analysis.The bar graphs for each paper show the distribution of readership levels among subdisciplines.17 of the 21 CS subdisciplines are represented and the axis scales and color schemes remain constant throughout.This is perhaps expected for such a general purpose technique, but given the above it’s strange that there are no AI readers of this paper at all.In this paper, Google founders Sergey Brin and Larry Page discuss how Google was created and how it initially worked.The importance of the monolithic “Big Iron” supercomputer has been on the wane for decades.The interesting thing about this paper is that had some of the lowest readership scores of the top papers within a subdiscipline, but folks from across the entire spectrum of computer science are reading it.I was surprised to see this paper as number one instead of Shannon’s information theory paper (#7) or the paper describing the concept that became Google (#3).It turns out that interest in this paper is very strong among those who list artificial intelligence as their subdiscipline.