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, July 17, 2017 (7:00 AM) to Sunday, July 23, 2017 (6:00 PM)

Monday, July 17, 2017
8:50 AM Opening words
Opening words
8:50 AM - 9:00 AM
Room: Reading University
Contributions

8:50 AM 'Welcome to MLHEP' Opening Words - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU)) Ulrik Egede (Imperial College (GB))
9:00 AM Day 1 Lectures
Day 1 Lectures
9:00 AM - 10:30 AM
Room: Reading University
Contributions

9:00 AM Lecture 1. Introduction. Why ML works. Overfitting. Model Selection. Figures of Merits. Linear Models. Regularization. Logistic Regression. - Alexey Artemov (Yandex)
10:30 AM Coffee break
Coffee break
10:30 AM - 10:50 AM
Room: Reading University
10:50 AM Competition Introduction
Competition Introduction
10:50 AM - 11:10 AM
Room: Reading University
Contributions

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

11:10 AM Seminar 1. Python data crunching: numpy, root_numpy, pandas (very short), matplotlib. - Alexander Panin (Yandex School of Data Analysis (RU))
12:40 PM Lunch
Lunch
12:40 PM - 2:00 PM
Room: Reading University
2:00 PM Day 1 Lectures
Day 1 Lectures
2:00 PM - 3:30 PM
Room: Reading University
Contributions

2:00 PM Lecture 2. Decision Trees. Bagging. Ensembles. RandomForest. AdaBoost. GB-Reweighting. Gradient Boosting. Decorrelation of features with predictions. - Alexey Artemov (Yandex)
3:30 PM Coffee break
Coffee break
3:30 PM - 3:50 PM
Room: Reading University
3:50 PM Day 1 Seminars
Day 1 Seminars
3:50 PM - 5:20 PM
Room: Reading University
Contributions

3:50 PM Seminar 2. Matplotlib, Trees & Linear Models in SciKit Learn. Overfitting checks & prevention. - Alexander Panin (Yandex School of Data Analysis (RU))
7:00 PM Welcome Reception
Welcome Reception
7:00 PM - 8:30 PM
Room: Reading University
Tuesday, July 18, 2017
9:00 AM Day 2 Lectures
Day 2 Lectures
9:00 AM - 10:30 AM
Room: Reading University
Contributions

9:00 AM Lecture 3. Ensembling: Adaboost, Stacking. Gradient Boosting.
10:30 AM Coffee break
Coffee break
10:30 AM - 11:00 AM
Room: Reading University
11:00 AM Day 2 Seminars
Day 2 Seminars
11:00 AM - 12:30 PM
Room: Reading University
Contributions

11:00 AM Seminar 3. Ensembling: Adaboost, Stacking. Gradient Boosting.
12:30 PM Lunch
Lunch
12:30 PM - 1:30 PM
Room: Reading University
1:30 PM Day 2 Lectures
Day 2 Lectures
1:30 PM - 3:00 PM
Room: Reading University
Contributions

1:30 PM Lecture 4. Hyperparameters optimization techniques and methods. Feature selection. TPE. Gaussian Processes
3:00 PM Coffee break
Coffee break
3:00 PM - 3:30 PM
Room: Reading University
3:30 PM Day 2 seminrs
Day 2 seminrs
3:30 PM - 5:00 PM
Room: Reading University
Contributions

3:30 PM Seminar 4. Optimization of hyper-parameters, applications to challenge.
5:00 PM Break
Break
5:00 PM - 5:15 PM
Room: Reading University

5:15 PM Mike Williams
Mike Williams
5:15 PM - 6:45 PM
Room: Reading University
Wednesday, July 19, 2017

9:00 AM

9:00 AM - 9:00 PM
Room: Reading University
Thursday, July 20, 2017
9:00 AM Day 4 Lectures
Day 4 Lectures
9:00 AM - 10:30 AM
Room: Reading University
Contributions

9:00 AM Lecture 5. Introduction into Neural Network models. Multi-layered Perceptron. Backpropagation.
10:30 AM Coffee break
Coffee break
10:30 AM - 11:00 AM
Room: Reading University
11:00 AM Day 4 Seminars
Day 4 Seminars
11:00 AM - 12:30 PM
Room: Reading University
Contributions

11:00 AM Seminar 5. Computing gradient by hand. Tensorflow. Keras. Remote machine setup. Getting familiar with GPU.
12:30 PM Lunch
Lunch
12:30 PM - 1:30 PM
Room: Reading University
1:30 PM Day 4 Lectures
Day 4 Lectures
1:30 PM - 3:00 PM
Room: Reading University
Contributions

1:30 PM Lecture 6. Intro into Deep learning. Convolutional Neural Network. Model zoo. Augmentation.
3:00 PM Coffee break
Coffee break
3:00 PM - 3:30 PM
Room: Reading University
3:30 PM Day 4 Seminars
Day 4 Seminars
3:30 PM - 5:00 PM
Room: Reading University
Contributions

3:30 PM Seminar 6. Image recognition using convolutional neural networks.
5:00 PM Break
Break
5:00 PM - 5:15 PM
Room: Reading University
5:15 PM Guest Lecture
Guest Lecture
5:15 PM - 6:45 PM
Room: Reading University
Contributions

5:15 PM Guest Lecture - Noel Dawe (University of Melbourne (AU))
Friday, July 21, 2017

9:00 AM ML Projects & Problems @ HEP
ML Projects & Problems @ HEP
9:00 AM - 10:30 AM
Room: Reading University

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

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

12:30 PM Lunch
Lunch
12:30 PM - 1:30 PM
Room: Reading University
1:30 PM Day 5 Lectures
Day 5 Lectures
1:30 PM - 3:00 PM
Room: Reading University
Contributions

1:30 PM Lecture 7. Dimensionality Reduction. PCA. LDA. LLE. TSNE. Autoencoders.
3:00 PM Coffee break
Coffee break
3:00 PM - 3:30 PM
Room: Reading University
3:30 PM Day 5 Seminars
Day 5 Seminars
3:30 PM - 5:00 PM
Room: Reading University
Contributions

3:30 PM Seminar 7. PCA, Autoencoders (faces)
5:00 PM Break
Break
5:00 PM - 5:15 PM
Room: Reading University

5:15 PM Tim Head
Tim Head
5:15 PM - 6:45 PM
Room: Reading University

7:00 PM Dinner
Dinner
7:00 PM - 9:00 PM
Saturday, July 22, 2017
9:00 AM Day 6 Lectures
Day 6 Lectures
9:00 AM - 10:30 AM
Room: Reading University
Contributions

9:00 AM Lecture 8 Generative Adversarial Networks, Metric Learning.
10:30 AM Coffee break
Coffee break
10:30 AM - 11:00 AM
Room: Reading University
11:00 AM Day 6 Seminars
Day 6 Seminars
11:00 AM - 12:30 PM
Room: Reading University
Contributions

11:00 AM Seminar 8 Generative Adversarial Networks (physics)
12:30 PM Lunch
Lunch
12:30 PM - 1:30 PM
Room: Reading University
1:30 PM Day 6 Lectures
Day 6 Lectures
1:30 PM - 4:00 PM
Room: Reading University
Contributions

1:30 PM Lecture 9. RNNs.

3:30 PM Certificates, Free Discussion
Sunday, July 23, 2017

9:00 AM Lecture 10. Why Deep Learning works. Tips & tweaks.
Lecture 10. Why Deep Learning works. Tips & tweaks.
9:00 AM - 10:30 AM
Room: Reading University

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

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

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