Name: Second Machine Learning in High Energy Physics Summer School 2016
Start: 2016-06-20T08:00:00+02:00
End: 2016-06-26T19:00:00+02:00
Location: Lund University

Second Machine Learning in High Energy Physics Summer School 2016

from Monday 20 June 2016 (08:00) to Sunday 26 June 2016 (19:00)

Monday 20 June 2016
09:00 Welcome
Welcome
09:00 - 10:20
Room: Lundmarkssalen
Contributions

09:00 Registration

09:30 Welcome to MLHEP - Caterina Doglioni (Lund University (SE))

09:50 Competition introduction
10:20 Day 1 lectures
Day 1 lectures
10:20 - 13:20
Room: Lundmarkssalen
Contributions

10:20 Intro: General pipeline, ML at a glance, model evaluation

12:00 Metric ML algorithms
13:20 Lunch
Lunch
13:20 - 14:35
Room: Lundmarkssalen
14:35 Day 1 seminars
Day 1 seminars
14:35 - 17:35
Room: Lundmarkssalen
Contributions

14:35 Course technicalities, working environment

16:15 Python for data analysis; Probability density estimation
17:35 Break
Break
17:35 - 17:55
Room: Lundmarkssalen

17:55 Jet parton and particle identification and applications
Jet parton and particle identification and applications
17:55 - 19:00
Room: Lundmarkssalen

20:00 Welcome dinner
Welcome dinner
20:00 - 21:30
Tuesday 21 June 2016
09:30 Day 2 lectures
Day 2 lectures
09:30 - 12:30
Room: Lundmarkssalen
Contributions

09:30 Decision trees

11:10 Ensembles
12:30 Lunch
Lunch
12:30 - 13:30
Room: Lundmarkssalen
13:30 Day 2 seminrs
Day 2 seminrs
13:30 - 16:30
Room: Lundmarkssalen
Contributions

13:30 Model evaluation

15:10 sklearn, simple algorithms
16:30 Break
Break
16:30 - 16:50
Room: Lundmarkssalen

16:50 Online, Collaborative Machine Learning
Online, Collaborative Machine Learning
16:50 - 18:00
Room: Lundmarkssalen
Wednesday 22 June 2016
09:30 Day 3 lectures
Day 3 lectures
09:30 - 12:30
Room: Lundmarkssalen
Contributions

09:30 Feature engineering, Dimensionality reduction

11:10 Hyperparameters search
12:30 Lunch
Lunch
12:30 - 13:30
Room: Lundmarkssalen
13:30 Day 3 seminars
Day 3 seminars
13:30 - 15:10
Room: Lundmarkssalen
Contributions

13:30 Ensemble algorithms, dimensionality reduction
15:10 Data Doping solution to the "Flavour of Physics" Kaggle challenge
Data Doping solution to the "Flavour of Physics" Kaggle challenge
15:10 - 16:10
Room: Lundmarkssalen

16:10 Break
Break
16:10 - 16:30
Room: Lundmarkssalen

16:30 Approximating Likelihood Ratios with Calibrated Classifiers (TBC)
Approximating Likelihood Ratios with Calibrated Classifiers (TBC)
16:30 - 17:30
Room: Lundmarkssalen
Thursday 23 June 2016
09:30 Day 4 lectures
Day 4 lectures
09:30 - 11:10
Room: Lundmarkssalen
Contributions

09:30 Boosting reweighting and flatness
11:10 Boosting reweighting and flatness - seminar
Boosting reweighting and flatness - seminar
11:10 - 12:30
Room: Lundmarkssalen

12:30 Lunch
Lunch
12:30 - 13:30
Room: Lundmarkssalen
14:00 Day 4 seminars
Day 4 seminars
14:00 - 19:20
Room: H418, RYDBERGSALEN
Contributions

14:00 Feature engineering and selection - Nikita Kazeev (Yandex School of Data Analysis (RU))

15:40 Shallow neural networks - Alexander Panin (Yandex School of Data Analysis (RU))

17:20 Deep neural networks - Alexander Panin (Yandex School of Data Analysis (RU))
Friday 24 June 2016

09:00 Midsommar
Midsommar
09:00 - 21:00
Room: Lundmarkssalen
Saturday 25 June 2016
09:30 Deep learning
Deep learning
09:30 - 12:30
Room: Lundmarkssalen
Contributions

09:30 Deep learning I - Alexander Panin (Yandex School of Data Analysis (RU))

11:10 Deep learning II - Alexander Panin (Yandex School of Data Analysis (RU))
12:30 Lunch
Lunch
12:30 - 13:30
Room: Lundmarkssalen
13:30 Deep learning
Deep learning
13:30 - 16:30
Room: Lundmarkssalen
Contributions

13:30 Deep learning III - Alexander Panin (Yandex School of Data Analysis (RU))

15:10 Deep learning IV - Alexander Panin (Yandex School of Data Analysis (RU))
16:30 Break
Break
16:30 - 16:50
Room: Lundmarkssalen

16:50 Ultra High Energy Cosmic Rays and the CRAYFIS Experiment
Ultra High Energy Cosmic Rays and the CRAYFIS Experiment
16:50 - 17:50
Room: Lundmarkssalen
Sunday 26 June 2016
09:30
09:30 - 18:30
Room: Lundmarkssalen
Contributions

09:30 Challenge hacking

11:10 Challenge hacking

15:00 Presentations preparation

16:00 Awards and best solutions presentations

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