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)
Reading (Reading University)

        : Sessions
    /     : Talks
        : Breaks
Jul 17, 2017
Jul 18, 2017
Jul 19, 2017
Jul 20, 2017
Jul 21, 2017
Jul 22, 2017
Jul 23, 2017
AM
8:50 AM
Organisational - Ulrik Egede (Imperial College (GB)) Andrey Ustyuzhanin (Yandex School of Data Analysis (RU)) (until 9:00 AM) (Reading University)
8:50 AM 'Welcome to MLHEP' Opening Words - Ulrik Egede (Imperial College (GB)) Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))   (Reading University)
9:00 AM
Lectures - Alexey Artemov (Yandex) (until 10:30 AM) (Reading University)
9:00 AM Lecture 1. Introduction. Why ML works. Overfitting. Model Selection. Figures of Merits. Linear Models. Regularization. Logistic Regression. - Alexey Artemov (Yandex)   (Reading University)
10:30 AM --- Coffee break ---
10:50 AM
Practice: challenge & industry - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU)) (until 11:10 AM) (Reading University)
10:50 AM Competition Introduction - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))   (Reading University)
11:10 AM
Seminars - Alexander Panin (Yandex School of Data Analysis (RU)) (until 12:40 PM) (Reading University)
11:10 AM Seminar 1. Python data crunching: numpy, root_numpy, pandas (very short), matplotlib. - Alexander Panin (Yandex School of Data Analysis (RU))   (Reading University)
9:00 AM
Lectures (until 10:30 AM) (Reading University)
9:00 AM Lecture 3. Ensembling: Adaboost, Stacking. Gradient Boosting.   (Reading University)
10:30 AM --- Coffee break ---
11:00 AM
Seminars (until 12:30 PM) (Reading University)
11:00 AM Seminar 3. Ensembling: Adaboost, Stacking. Gradient Boosting.   (Reading University)
9:00 AM
Free day (until 9:00 PM) (Reading University)
9:00 AM
Lectures (until 10:30 AM) (Reading University)
9:00 AM Lecture 5. Introduction into Neural Network models. Multi-layered Perceptron. Backpropagation.   (Reading University)
10:30 AM --- Coffee break ---
11:00 AM
Seminars (until 12:30 PM) (Reading University)
11:00 AM Seminar 5. Computing gradient by hand. Tensorflow. Keras. Remote machine setup. Getting familiar with GPU.   (Reading University)
9:00 AM
Practice: challenge & industry (until 10:30 AM) (Reading University)
10:30 AM --- Coffee break ---
11:00 AM
Practice: challenge & industry (until 12:30 PM) (Reading University)
9:00 AM
Lectures (until 10:30 AM) (Reading University)
9:00 AM Lecture 8 Generative Adversarial Networks, Metric Learning.   (Reading University)
10:30 AM --- Coffee break ---
11:00 AM
Seminars (until 12:30 PM) (Reading University)
11:00 AM Seminar 8 Generative Adversarial Networks (physics)   (Reading University)
9:00 AM Lecture 10. Why Deep Learning works. Tips & tweaks.   (Reading University)
10:30 AM --- Break ---
11:00 AM
Practice: challenge & industry (until 12:00 PM) (Reading University)
PM
12:40 PM
Organisational (until 2:00 PM) (Reading University)
2:00 PM
Lectures - Alexey Artemov (Yandex) (until 3:30 PM) (Reading University)
2:00 PM Lecture 2. Decision Trees. Bagging. Ensembles. RandomForest. AdaBoost. GB-Reweighting. Gradient Boosting. Decorrelation of features with predictions. - Alexey Artemov (Yandex)   (Reading University)
3:30 PM --- Coffee break ---
3:50 PM
Seminars - Alexander Panin (Yandex School of Data Analysis (RU)) (until 5:20 PM) (Reading University)
3:50 PM Seminar 2. Matplotlib, Trees & Linear Models in SciKit Learn. Overfitting checks & prevention. - Alexander Panin (Yandex School of Data Analysis (RU))   (Reading University)
7:00 PM
Organisational (until 8:30 PM) (Reading University)
12:30 PM
Organisational (until 1:30 PM) (Reading University)
1:30 PM
Lectures (until 3:00 PM) (Reading University)
1:30 PM Lecture 4. Hyperparameters optimization techniques and methods. Feature selection. TPE. Gaussian Processes   (Reading University)
3:00 PM --- Coffee break ---
3:30 PM
Seminars (until 5:00 PM) (Reading University)
3:30 PM Seminar 4. Optimization of hyper-parameters, applications to challenge.   (Reading University)
5:00 PM
Organisational (until 5:15 PM) (Reading University)
5:15 PM
Invited lectures (until 6:45 PM) (Reading University)
12:30 PM
Organisational (until 1:30 PM) (Reading University)
1:30 PM
Lectures (until 3:00 PM) (Reading University)
1:30 PM Lecture 6. Intro into Deep learning. Convolutional Neural Network. Model zoo. Augmentation.   (Reading University)
3:00 PM --- Coffee break ---
3:30 PM
Seminars (until 5:00 PM) (Reading University)
3:30 PM Seminar 6. Image recognition using convolutional neural networks.   (Reading University)
5:00 PM
Organisational (until 5:15 PM) (Reading University)
5:15 PM
Invited lectures (until 6:45 PM) (Reading University)
5:15 PM Guest Lecture - Noel Dawe (University of Melbourne (AU))   (Reading University)
12:30 PM
Organisational (until 1:30 PM) (Reading University)
1:30 PM
Lectures (until 3:00 PM) (Reading University)
1:30 PM Lecture 7. Dimensionality Reduction. PCA. LDA. LLE. TSNE. Autoencoders.   (Reading University)
3:00 PM --- Coffee break ---
3:30 PM
Seminars (until 5:00 PM) (Reading University)
3:30 PM Seminar 7. PCA, Autoencoders (faces)   (Reading University)
5:00 PM
Organisational (until 5:15 PM) (Reading University)
5:15 PM
Invited lectures (until 6:45 PM) (Reading University)
7:00 PM --- Dinner ---
12:30 PM
Organisational (until 1:30 PM) (Reading University)
1:30 PM
Lectures (until 4:00 PM) (Reading University)
1:30 PM Lecture 9. RNNs.   (Reading University)
3:00 PM --- Coffee break ---
3:30 PM Certificates, Free Discussion   (Reading University)