Calorimeter Machine Learning

Name: Calorimeter Machine Learning
Start: 2017-08-31T19:00:00+02:00
End: 2017-08-31T21:20:00+02:00
Location: No location set

Thursday 31 Aug 2017, 19:00 → 21:20 Europe/Zurich

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Summary:

1. Matt presented the BDT results of the gamma vs. pi0 classifier. ECALmomentY5 still contributed more than ECALmomentX5 (without adding subjettiness).

2. Doubling the training sample size for electron vs. charged pion classifier to 400K did not increase the accuracy. Maybe we need more training data?

3. A faster generator will be released.

4. We also debugged the code for subjettiness.

There are minutes attached to this event. Show them.

- 19:00 → 19:20
  
  Maurizio 20m
  
  Speaker: Maurizio Pierini (CERN)
- 19:20 → 19:40
  
  Ben 20m
  
  Speaker: Benjamin Henry Hooberman (Univ. Illinois at Urbana-Champaign (US))
- 19:40 → 20:00
  
  Amir 20m
  
  Speaker: Amir Farbin (University of Texas at Arlington (US))
- 20:00 → 20:20
  
  Jean-Roch 20m
  
  Speaker: Dr Jean-Roch Vlimant (California Institute of Technology (US))
- 20:20 → 20:40
  
  Ryan 20m
  
  Speaker: Ryan Reece (University of California,Santa Cruz (US))
- 20:40 → 21:00
  
  Matt 20m
  
  Speaker: Matt Zhang (Univ. Illinois at Urbana-Champaign (US))
- 21:00 → 21:20
  
  Taylor 20m