[Ml-stat-talks] Fwd: Wilks Statistics Seminar: Aarti Singh, Friday, October. 16th @ 12:30
bee at princeton.edu
Mon Oct 12 11:41:06 EDT 2015
Talk of interest on Friday.
---------- Forwarded message ----------
From: Carol Smith <carols at princeton.edu>
Date: Mon, Oct 12, 2015 at 10:00 AM
Subject: Wilks Statistics Seminar: Aarti Singh, Friday, October. 16th @
To: wilks-seminar at princeton.edu
*** Wilks Statistics Seminar ***
DATE: Friday, October 16, 2015
LOCATION: Sherrerd Hall, room 101
SPEAKER: Aarti Singh, Carnegie Mellon University
TITLE: Power of Active Sampling for Statistical Learning
ABSTRACT: Most modern datasets are plagued with missing data or limited
sample sizes. However, in many applications, we have control over the data
sampling process such as which drug-gene interactions to record, which
network routes to probe, which movies to rate, etc. Thus, we can ask the
question – what does the freedom to actively sample data in a
feedback-driven manner buy us?
In this talk, I will present recent work by my group on active sampling
methods for several statistical learning problems such as matrix and tensor
completion/approximation, column subset selection, learning structure of
graphical models, and clustering, as time permits. I will quantify the
precise reduction in the amount of data needed to achieve a desired
statistical error, as well as demonstrate that active sampling often also
enables us to handle a larger class of models such as matrices with
coherent row or column space and clusters at finer resolutions, when
compared to passive (non-feedback driven) sampling.
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