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08:30
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--- Registration ---
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09:00
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Welcome
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09:10
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HEP challenges
-
Marcin Chrzaszcz
(Universitaet Zuerich (CH), Institute of Nuclear Physics (PL))
(until 12:30)
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09:10
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Data Science at LHCb
-
Tim Head
(Ecole Polytechnique Federale de Lausanne (CH))
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09:50
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Summary of «Flavors of Physics» Challenge
-
Andrey Ustyuzhanin
(Yandex School of Data Analysis (RU))
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10:30
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--- Coffee Break ---
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10:50
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Data Doping solution for "Flavours of Physics" challenge
- Dr
Vicens Gaitan
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11:30
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Transfer Learning solution for "Flavours of Physics" challenge
- Dr
Alexander Rakhlin
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11:50
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Pitfalls of evaluating a classifier's performance in high energy physics applications
- Dr
Gilles Louppe
(New York University (US))
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09:00
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Data Science Applications
-
Tim Head
(Ecole Polytechnique Federale de Lausanne (CH))
(until 12:30)
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09:00
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Classifier output calibration to probability
-
Tatiana Likhomanenko
(National Research Centre Kurchatov Institute (RU))
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09:40
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Classifiers for centrality determination in proton-nucleus and nucleus-nucleus collisions
-
Igor Altsybeev
(St. Petersburg State University (RU))
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10:00
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Data Fusion Surogate Modeling on Incomplete Factorial Design of Experiments
- Prof.
Eugene Burnaev
(IITP)
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10:40
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--- Coffee Break ---
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11:00
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Mathematics of Big Data
- Prof.
Dmitry Vetrov
(Skoltech, Yandex School of Data Analysis, Higher School of Economics)
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11:40
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Efficient Elastic Net Regularization for Sparse Linear Models in the Multilabel Setting
- Mr
Zachary Chase Lipton
(University of California, Amazon)
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12:10
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Optimized Methods to Apply Neural Networks in HEP
-
Lev Dudko
(M.V. Lomonosov Moscow State University (RU))
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09:00
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Data Science Applications
-
Marc Olivier Bettler
(CERN)
(until 11:50)
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09:00
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Automatic Tuning of Hyperparameters
- Mr
Alexander Fonarev
(Skoltech)
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09:40
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Deep Learning for event reconstruction
-
Amir Farbin
(University of Texas at Arlington (US))
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10:20
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--- Coffee Break ---
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10:40
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Fast multimodal clustering: searching for optimal patterns
- Dr
Dmitry Ignatov
(HSE)
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11:20
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Summary of open space discussions
-
Andrey Ustyuzhanin
(Yandex School of Data Analysis (RU))
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11:45
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Machine Learning tools & tutorials
-
Andrey Ustyuzhanin
(Yandex School of Data Analysis (RU))
(until 12:40)
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11:50
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Nvidia tutorial
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12:00
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TensorFlow introduction & tutorial #1
-
Rafal Jozefowicz
(Google)
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12:30
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--- Lunch ---
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13:30
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HEP challenges discussions
-
Andrey Ustyuzhanin
(Yandex School of Data Analysis (RU))
(until 15:00)
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15:00
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Machine Learning tools & tutorials
-
Andrey Ustyuzhanin
(Yandex School of Data Analysis (RU))
(until 19:00)
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15:00
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An introduction to machine learning with Scikit-Learn
- Dr
Gilles Louppe
(New York University (US))
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17:00
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--- Cofee break ---
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17:20
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Boosting applications for HEP
-
Aleksei Rogozhnikov
(Yandex School of Data Analysis (RU))
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19:00
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--- Reception/Dinner ---
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12:30
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--- Lunch ---
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13:30
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HEP challenges discussions
-
Andrey Ustyuzhanin
(Yandex School of Data Analysis (RU))
(until 15:00)
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15:00
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Machine Learning tools & tutorials
(until 18:50)
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15:00
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OpenML: Collaborative machine learning
- Dr
Joaquin Vanschoren
(https://www.tue.nl)
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15:40
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--- Coffee break ---
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16:10
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Calibration curves as tool to test for over- and underfitting
- Dr
Artem Vorozhtsov
(Yandex)
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16:30
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Reproducible Experiment Platform & Everware
-
Aleksei Rogozhnikov
(Yandex School of Data Analysis (RU))
Andrey Ustyuzhanin
(Yandex School of Data Analysis (RU))
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12:40
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--- Lunch ---
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13:30
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Machine Learning tools & tutorials
(until 14:50)
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13:30
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TensorFlow introduction & tutorial. Continuation
-
Rafal Jozefowicz
(Google)
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14:50
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Closing Remarks
-
Andrey Ustyuzhanin
(Yandex School of Data Analysis (RU))
Marcin Chrzaszcz
(Universitaet Zuerich (CH), Institute of Nuclear Physics (PL))
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