Posted by Phil LongMachine Learning is a branch of Artificial Intelligence in which, naturally enough, the aim is to get computers to learn: things like improving performance over time, and recognizing general tendencies among a number of specific cases. We have many ways to exploit Machine Learning programs, and a lot of data to give them. Machine Learning helps us to estimate what content users like most, what content is even legitimate, and how to match ads to content. It also plays key roles...
Tuesday, 20 May 2008
Tuesday, 6 May 2008
Can You Publish at Google?
Posted on 15:10 by Unknown
Posted by Rich GossweilerAs part of the interview process at Google we try to describe what it is like to do research here. A common question I get is "How hard is it to publish at Google?" I want to dispel the myth that it is hard. It is easy to publish, easy to put code into open source, easy to give talks, etc. But it is also easy for great research to become great engineering, and that is an incredible lure. Great barriers of despair exist between research and development at many companies; researchers can find it hard to have impact beyond...
Thursday, 1 May 2008
VisualRank
Posted on 13:30 by Unknown
Posted by Shumeet Baluja and Yushi JingAt WWW-2008, in Beijing, China, we presented our paper "PageRank for Product Image Search". In this paper, we presented a system that used visual cues, instead of solely text information, to determine the rank of images. The idea was simple: find common visual themes in a set of images, and then find a small set of images that best represented those themes. The resulting algorithm wound up being PageRank, but on an entirely inferred graph of image similarities. Since the release of the paper, we've noticed...
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