IML Machine Learning Working Group: open topic
Agenda under development. If you like to present, please contact iml.coordinators@cern.ch
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2:00 PM
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Seminar
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2:00 PM
EP-IT data science seminar: Soumith Chintala (Facebook): Automatic Differentiation and Deep Learning PLEASE JOIN THIS SESSION THROUGH WEBCAST FROM THE SEMINAR PAGE 1h
https://indico.cern.ch/event/689421/
Statistical learning has been getting more and more interest from the particle-physics community in recent times, with neural networks and gradient-based optimization being a focus.
In this talk we shall discuss three things:
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automatic differention tools: tools to quickly build DAGs of computation that are fully differentiable. We shall focus on one such tool "PyTorch".
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Easy deployment of trained neural networks into large systems with many constraints: for example, deploying a model at the reconstruction phase where the neural network has to be integrated into CERN's bulk data-processing C++-only environment
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Some recent models in deep learning for segmentation and generation that might be useful for particle physics problems.
Please note that a Webcast retransmission will be available for this Seminar.
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2:00 PM
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3:00 PM
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6:00 PM
Regular IML meeting
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3:00 PM
News and group updates 10mSpeakers: Lorenzo Moneta (CERN), Markus Stoye (CERN), Michele Floris (CERN), Paul Seyfert (CERN), Steven Randolph Schramm (Universite de Geneve (CH))
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3:10 PM
ROC's, AUC's and alternatives in HEP and other domains 30mSpeaker: Andrea Valassi (CERN)
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3:40 PM
Riemann-Theta Boltzmann Machine 20m
https://arxiv.org/abs/1712.07581
Speakers: Daniel Krefl (CERN), Daniel Krefl (Unknown), Stefano Carrazza (CERN) -
4:00 PM
Conference report: NIPS 20mSpeaker: Savannah Jennifer Thais (Yale University (US))
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4:40 PM
Minutes 1m
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3:00 PM
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2:00 PM
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3:00 PM