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Activity Number: 552
Type: Contributed
Date/Time: Wednesday, August 12, 2015 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Learning and Data Mining
Abstract #316058
Title: Online Statistical Learning Algorithms
Author(s): Joshua Day*
Companies: North Carolina State University
Keywords: online algorithm ; statistical learning ; penalized regression
Abstract:

Many statistical models have limited use with data too large to hold in memory or arriving in a stream. We introduce a variety of online or one-pass algorithms for statistical learning suited to these applications. The online nature of these algorithms allow us to create a family of self-tuning models. At each time point (epoch), two batches of data are held in computer memory; The two batches serve as training set and test set, and tuning parameters are adjusted at each epoch.


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