In the wake of last year’s Ideological Search success, the team at Yahoo Labs did our best yesterday to further our understanding of deep April Fool’s science. We used sophisticated methods from context-insensitive grammars, nonlinear pessimization and pseudorandom variables.
David Reiley kicked of the 2010 India Big Thinkers Series on March 19th presenting "Does Retail Advertising Work? Measuring the Effects of Advertising on Sales via a Controlled Experiment on Yahoo".
Yahoo has built a new tool for this year’s tournament intended to determine which of these results are most likely.
We invite you to join a new experiment we cooked up at Yahoo Labs called Predictalot, a game that takes NCAA tournament pick ‘em to entirely new extremes.
Forget the brackets in the office NCAA Tournament pool. This year, Yahoo is offering an application drawing on the wisdom of crowds to make sense out of March Madness.
The responsibility to earn and keep our users’ trust is not just a matter of Yahoo policy (although that is critical too), it’s also a technical challenge that requires scientific innovation to continuously improve and maintain.
Even though machine learning has such a broad influence on the Internet, it can be quite difficult to recognize. This is primarily because machine learning’s benefits are often hidden -- they are the spam emails you don't see, the uninteresting news articles you don't see, and the irrelevant search results you don't see, just to name a few.
Although social networking and content aggregation seem like different applications, at the core they share a key mechanism: collecting the most recent content from a set of producers, and distributing it to a set of consumers.
Andrei Broder is recognized for his contributions to the science and engineering of the World Wide Web.