IML Machine Learning Workshop

Session

Closing Session

22 Mar 2017, 16:30

222/R-001 (CERN)

Conveners

Closing Session: Wrap-up, Hands-on Challenge Results

• Paul Seyfert (Universita & INFN, Milano-Bicocca (IT))
• Michele Floris (CERN)

17. HEP.TrkX [Vidyo]

Dustin James Anderson (California Institute of Technology (US))

22/03/2017, 16:30

Reconstruction of charged particle tracks is a central task in the processing of physics data at the LHC and other colliders. Current state-of-the-art tracking algorithms are based on the Kalman filter and have seen great success both offline and at trigger level. However, these algorithms scale poorly with increasing detector occupancy, and it is foreseen that significant changes will be...

18. Object identification with deep learning using Intel DAAL on Knights Landing processor [Vidyo]

David Nonso Ojika (University of Florida (US))

22/03/2017, 17:05

The problem of object recognition is computationally expensive, especially when large amounts of data is involved. Recently, techniques in deep neural networks (DNN) - including convolutional neural networks and residual neural networks - have shown great recognition accuracy compared to traditional methods (artificial neural networks, decision tress, etc.). However, experience reveals that...

20. Close-out

Steven Randolph Schramm (Universite de Geneve (CH))

22/03/2017, 17:30

19. Challenge results