“Designing Futures Where Nothing Will Occur”: The Art of Forecasting

Filed in Machine Learning, Technology

One of the key analytics products we provide is robust time-series forecasting over multidimensional faceted data, which requires giving users access to a number of predictions exponential in the base data dimensionality. For online publishers, such forecasting includes simple metrics like impressions, revenue and actions, and more generally we might want to model CTR or more complex metrics like the opportunity cost of showing house ads versus sponsorship ads. Existing forecasting systems tend to exist inside of traditional OLAP storage offerings that embed a limited set of statistical functions, many of which are poorly optimized and slow to execute. The […]

“Designing Futures Where Nothing Will Occur”:  The Art of Forecasting
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Hacking Hacker News Headlines

Filed in Fun, Machine Learning, Technology

One weekend a few months ago Vad [1] and I were hanging around the new Metamarkets office reading Hacker News.  We noticed something strange: two different headlines, both linking to identical content, resulted in dramatically different popularity ranks.  Do headlines matter so much? What drives observed popularity? We started to investigate. (Above: Rolling 10 days of article ranks. Click for an interactive version.)

Hacking Hacker News Headlines
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Why Generic Machine Learning Fails

Filed in Machine Learning, Musings, Technology

Inside the Belly of a Beast I’ve been lucky enough to have spent a significant chunk of my time over the past five years hacking the machine learning stack at Google. It is every bit as awesome, magical and fearsome as you can imagine. It is, very literally, the beating heart of one of the world’s largest economies; it’s immensely complex, it can’t be turned off and classification error is measured in money. Fundamentally, it’s the model for practical machine learning, and there is a lot of insight to be gleaned from recent work there. In terms of availability and […]

Why Generic Machine Learning Fails
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