Monday, November 29, 2010 - 8:45am - 10:15am
Ricardo Nochetto (University of Maryland)
Adaptivity is an essential tool in modern scientific and
engineering computation that allows one to optimize the
computational effort by locating the degrees of freedom where
they are most needed, that is in regions of rapid solution
variation. Adaptive finite element methods (AFEM) are the most
popular and effective numerical methods to solve elliptic PDE,
and are driven by a posteriori error estimators. In this tutorial
we will discuss the basic structure of AFEM and its main
Thursday, December 8, 2005 - 3:00pm - 4:00pm
Robert Nowak (University of Wisconsin, Madison)
Adaptive sampling, also called Active Learning, uses information
gleaned from previous measurements (e.g., feedback) to guide and focus
the sampling process. Theoretical and experimental results have shown
that adaptive sampling can dramatically outperform conventional
non-adaptive sampling schemes. I will review some of the most
encouraging theoretical results to date, and focus on new results
regarding the capabilities of adaptive sampling methods for learning
piecewise smooth functions. I will also contrast adaptive sampling
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