On 04 Nov 2015, at 15:13, Announcements of talks at IDSIA
<talks(a)idsia.ch> wrote:
Dear all,
You are invited to attend the following exciting talk at 11:30 AM on Tuesday, 17th Nov.
:
Title:
Deep Learning for High-Energy Physics
Abstract:
Soon after the discovery of the Higgs Boson was announced in 2012, the Large Hadron
Collider was shut down for two years of planned upgrades. Now it is back online, smashing
particles at even higher energies and producing a torrent of new data. Analyzing this data
is a great challenge, and the data-analysis pipelines make heavy use of machine learning.
In this talk, we will show how deep learning can improve the statistical power of this
analysis by automatically learning high-level representations of the data, rather than
relying on features that have been engineered by physicists.
Speaker Bio:
Peter Sadowski is a PhD student in the Department of Computer Science at the University
of California Irvine. His research interests are centered around machine learning and its
applications to the natural sciences, with a particular interest in deep learning and
artificial neural networks. His latest work focuses on the use of deep learning to analyze
particle physics data from the Large Hadron Collider.
Ciao,
Rupesh
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