Mel-li by nekdo zajem... (Pozn.: Predpokladam, ze pujde o pomerne odbornou prednasku.)
----- Forwarded message from Iveta.Mrazova@mff.cuni.cz -----
Vazeni studenti,
dovolte mi, prosim, pozvat Vas na prednasku "The Learning Behind Gmail Priority Inbox," kterou proslovi Ondrej Pacovsky (Google Inc., Zurich, Switzerland) v pondeli, 16. 5. v 10.50 na MFF UK (poslucharna S9 v 1. patre budovy na Malostranskem namesti 25). Abstrakt prednasky je pripojen pod carou.
Iveta Mrazova, KTIML MFF UK ==================================================================
Abstrakt prednasky ´The Learning Behind Gmail Priority Inbox:´
Many Gmail users receive tens or hundreds of mails per day. The Priority Inbox attempts to alleviate such information overload by learning a per-user statistical model of importance, and ranking mail by how likely the user is to act on that mail. This is not a new problem, however to do this at scale, performing real-time ranking and near-online updating of millions of models per day significantly complicates the problem.
The challenges include inferring the importance of mail without explicit user labelling; finding learning methods that deal with non-stationary and noisy training data; constructing models that reduce training data requirements; storing and processing terabytes of per-user feature data; and finally, predicting in a distributed and fault tolerant way.
While ideas were borrowed from the application of ML in Gmail spam detection, importance ranking is harder as users disagree on what is important, requiring a high degree of personalization. Because “importance” is highly personal, we try to predict it by learning a per-user statistical model, updated as frequently as possible. The result is one of the largest and most user facing applications of machine learning at Google.
Ref.: http://research.google.com/pubs/archive/36955.pdf
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