IML Machine Learning Working Group

Tuesday 5 May 2020, 16:00 → 18:00 Europe/Zurich

Zoom-only

Agenda under development. If you like to present, please contact iml.coordinators@cern.ch .  Meeting will be by zoom only.

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1 News

Speakers: Andrea Wulzer (CERN and EPFL), David Rousseau (LAL-Orsay, FR), Gian Michele Innocenti (CERN), Lorenzo Moneta (CERN), Loukas Gouskos (CERN), Paul Seyfert (CERN), Riccardo Torre (CERN)

News

2 Efficiency Parameterization with Neural Networks

Speakers: Francesco Armando Di Bello (Sapienza Universita e INFN, Roma I (IT)), Jonathan Shlomi (Weizmann Institute of Science (IL))

efNN_IML.pdf

link2paper

3 Adversarial domain adaptation to reduce sample bias in a classification ML algorithm

We apply adversarial domain adaptation to reduce sample bias in a classification machine learning algorithm. We add a gradient reversal layer to a neural network to simultaneously classify signal versus background events, while minimising the difference of the classifier response to a background sample using an alternative MC model. We show this on the example of simulated events at the LHC with $t\bar{t}H$ signal versus $t\bar{t}b\bar{b}$ background classification.

Speakers: Jose Manuel Clavijo Columbie (Deutsches Elektronen-Synchrotron (DE)), Judith Katzy (Deutsches Elektronen-Synchrotron (DE)), Paul Glaysher (DESY)

IML_05.05.2020_JoseClavijo.pdf

link2paper

4 IML Citation repository

Speakers: Ben Nachman (Lawrence Berkeley National Lab. (US)), Matthew Feickert (Univ. Illinois at Urbana Champaign (US))

2020-05-05.pdf