Name: Third Machine Learning in High Energy Physics Summer School 2017
Start: 2017-07-17T07:00:00+01:00
End: 2017-07-23T18:00:00+01:00
Location: Reading

Third Machine Learning in High Energy Physics Summer School 2017

from Monday 17 July 2017 (07:00) to Sunday 23 July 2017 (18:00)

Monday 17 July 2017
08:50 Opening words
Opening words
08:50 - 09:00
Room: Reading University
Contributions

08:50 'Welcome to MLHEP' Opening Words - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU)) Ulrik Egede (Imperial College (GB))
09:00 Day 1 Lectures
Day 1 Lectures
09:00 - 10:30
Room: Reading University
Contributions

09:00 Lecture 1. Introduction. Why ML works. Overfitting. Model Selection. Figures of Merits. Linear Models. Regularization. Logistic Regression. - Alexey Artemov (Yandex)
10:30 Coffee break
Coffee break
10:30 - 10:50
Room: Reading University
10:50 Competition Introduction
Competition Introduction
10:50 - 11:10
Room: Reading University
Contributions

10:50 Competition Introduction - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))
11:10 Day 1 Seminars
Day 1 Seminars
11:10 - 12:40
Room: Reading University
Contributions

11:10 Seminar 1. Python data crunching: numpy, root_numpy, pandas (very short), matplotlib. - Alexander Panin (Yandex School of Data Analysis (RU))
12:40 Lunch
Lunch
12:40 - 14:00
Room: Reading University
14:00 Day 1 Lectures
Day 1 Lectures
14:00 - 15:30
Room: Reading University
Contributions

14:00 Lecture 2. Decision Trees. Bagging. Ensembles. RandomForest. AdaBoost. GB-Reweighting. Gradient Boosting. Decorrelation of features with predictions. - Alexey Artemov (Yandex)
15:30 Coffee break
Coffee break
15:30 - 15:50
Room: Reading University
15:50 Day 1 Seminars
Day 1 Seminars
15:50 - 17:20
Room: Reading University
Contributions

15:50 Seminar 2. Matplotlib, Trees & Linear Models in SciKit Learn. Overfitting checks & prevention. - Alexander Panin (Yandex School of Data Analysis (RU))
19:00 Welcome Reception
Welcome Reception
19:00 - 20:30
Room: Reading University
Tuesday 18 July 2017
09:00 Day 2 Lectures
Day 2 Lectures
09:00 - 10:30
Room: Reading University
Contributions

09:00 Lecture 3. Ensembling: Adaboost, Stacking. Gradient Boosting.
10:30 Coffee break
Coffee break
10:30 - 11:00
Room: Reading University
11:00 Day 2 Seminars
Day 2 Seminars
11:00 - 12:30
Room: Reading University
Contributions

11:00 Seminar 3. Ensembling: Adaboost, Stacking. Gradient Boosting.
12:30 Lunch
Lunch
12:30 - 13:30
Room: Reading University
13:30 Day 2 Lectures
Day 2 Lectures
13:30 - 15:00
Room: Reading University
Contributions

13:30 Lecture 4. Hyperparameters optimization techniques and methods. Feature selection. TPE. Gaussian Processes
15:00 Coffee break
Coffee break
15:00 - 15:30
Room: Reading University
15:30 Day 2 seminrs
Day 2 seminrs
15:30 - 17:00
Room: Reading University
Contributions

15:30 Seminar 4. Optimization of hyper-parameters, applications to challenge.
17:00 Break
Break
17:00 - 17:15
Room: Reading University

17:15 Mike Williams
Mike Williams
17:15 - 18:45
Room: Reading University
Wednesday 19 July 2017

09:00

09:00 - 21:00
Room: Reading University
Thursday 20 July 2017
09:00 Day 4 Lectures
Day 4 Lectures
09:00 - 10:30
Room: Reading University
Contributions

09:00 Lecture 5. Introduction into Neural Network models. Multi-layered Perceptron. Backpropagation.
10:30 Coffee break
Coffee break
10:30 - 11:00
Room: Reading University
11:00 Day 4 Seminars
Day 4 Seminars
11:00 - 12:30
Room: Reading University
Contributions

11:00 Seminar 5. Computing gradient by hand. Tensorflow. Keras. Remote machine setup. Getting familiar with GPU.
12:30 Lunch
Lunch
12:30 - 13:30
Room: Reading University
13:30 Day 4 Lectures
Day 4 Lectures
13:30 - 15:00
Room: Reading University
Contributions

13:30 Lecture 6. Intro into Deep learning. Convolutional Neural Network. Model zoo. Augmentation.
15:00 Coffee break
Coffee break
15:00 - 15:30
Room: Reading University
15:30 Day 4 Seminars
Day 4 Seminars
15:30 - 17:00
Room: Reading University
Contributions

15:30 Seminar 6. Image recognition using convolutional neural networks.
17:00 Break
Break
17:00 - 17:15
Room: Reading University
17:15 Guest Lecture
Guest Lecture
17:15 - 18:45
Room: Reading University
Contributions

17:15 Guest Lecture - Noel Dawe (University of Melbourne (AU))
Friday 21 July 2017

09:00 ML Projects & Problems @ HEP
ML Projects & Problems @ HEP
09:00 - 10:30
Room: Reading University

10:30 Coffee break
Coffee break
10:30 - 11:00
Room: Reading University

11:00 ML at industry
ML at industry
11:00 - 12:30
Room: Reading University

12:30 Lunch
Lunch
12:30 - 13:30
Room: Reading University
13:30 Day 5 Lectures
Day 5 Lectures
13:30 - 15:00
Room: Reading University
Contributions

13:30 Lecture 7. Dimensionality Reduction. PCA. LDA. LLE. TSNE. Autoencoders.
15:00 Coffee break
Coffee break
15:00 - 15:30
Room: Reading University
15:30 Day 5 Seminars
Day 5 Seminars
15:30 - 17:00
Room: Reading University
Contributions

15:30 Seminar 7. PCA, Autoencoders (faces)
17:00 Break
Break
17:00 - 17:15
Room: Reading University

17:15 Tim Head
Tim Head
17:15 - 18:45
Room: Reading University

19:00 Dinner
Dinner
19:00 - 21:00
Saturday 22 July 2017
09:00 Day 6 Lectures
Day 6 Lectures
09:00 - 10:30
Room: Reading University
Contributions

09:00 Lecture 8 Generative Adversarial Networks, Metric Learning.
10:30 Coffee break
Coffee break
10:30 - 11:00
Room: Reading University
11:00 Day 6 Seminars
Day 6 Seminars
11:00 - 12:30
Room: Reading University
Contributions

11:00 Seminar 8 Generative Adversarial Networks (physics)
12:30 Lunch
Lunch
12:30 - 13:30
Room: Reading University
13:30 Day 6 Lectures
Day 6 Lectures
13:30 - 16:00
Room: Reading University
Contributions

13:30 Lecture 9. RNNs.

15:30 Certificates, Free Discussion
Sunday 23 July 2017

09:00 Lecture 10. Why Deep Learning works. Tips & tweaks.
Lecture 10. Why Deep Learning works. Tips & tweaks.
09:00 - 10:30
Room: Reading University

10:30 Break
Break
10:30 - 11:00
Room: Reading University

11:00 Awards & Winning solution presentation
Awards & Winning solution presentation
11:00 - 12:00
Room: Reading University

Choose timezone