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VERSION:2.0
PRODID:-//RLASKEY//CALENDEROUS//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20260920T225008Z
LAST-MODIFIED:20180402T133523Z
DTSTART:20180404T200000Z
DTEND:20180404T210000Z
UID:event1909@bu.edu
URL:http://physics.bu.edu/internal/events/show/1909
SUMMARY:"Modern Machine Learning in Particle Physics"
DESCRIPTION:Featuring Matthew Schwartz\, Harvard  University\n\nPart of the
	 HET Seminar Series.\n\nParticle physics involves an intense data science c
	hallenge: signals of interest\, like for the Higgs boson are often buried i
	n backgrounds trillions of times as large. Over the last decade or so\, the
	re has been a revolution in machine learning\, and over the last year or tw
	o\, the revolution has started to influence particle physics. For example\,
	 image recognition technology based on convolutional neural networks can be
	 used to find patterns in the distribution of energy around a detector. Or 
	recurrent neural networks designed for natural language processing can be a
	pplied to parse the substructure of jets. This talk will review some of the
	se developments and discuss some exciting possibilities for the future.
LOCATION:PRB 595\, 3 Cummington Mall\, 02215
STATUS:CONFIRMED
CLASS:PUBLIC
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