Tim Head
(Ecole Polytechnique Federale de Lausanne (CH))
18/02/2016, 09:10
Andrey Ustyuzhanin
(Yandex School of Data Analysis (RU))
18/02/2016, 09:50
Dr
Vicens Gaitan
18/02/2016, 10:50
Dr
Alexander Rakhlin
18/02/2016, 11:30
Dr
Gilles Louppe
(New York University (US))
18/02/2016, 11:50
Dr
Gilles Louppe
(New York University (US))
18/02/2016, 15:00
https://github.com/glouppe/tutorial-scikit-learn
Aleksei Rogozhnikov
(Yandex School of Data Analysis (RU))
18/02/2016, 17:20
Tatiana Likhomanenko
(National Research Centre Kurchatov Institute (RU))
19/02/2016, 09:00
Igor Altsybeev
(St. Petersburg State University (RU))
19/02/2016, 09:40
Centrality, as a geometrical property of the collision, is crucial for the physical interpretation of proton-nucleus and nucleus-nucleus experimental data. However, it cannot be directly accessed in event-by-event data analysis.
Contemporary methods of the centrality estimation in A-A and p-A collisions usually rely on a single detector (either on the signal in zero-degree calorimeters or on...
Prof.
Eugene Burnaev
(IITP)
19/02/2016, 10:00
This work concerns a construction of surrogate models for a specific aerodynamic data base. This data base is generally available from wind tunnel testing or from CFD aerodynamic simulations and contains aerodynamic coefficients for different flight conditions and configurations (such as Mach number, angle-of-attack, vehicle configuration angle) encountered over different space vehicles...
Prof.
Dmitry Vetrov
(Skoltech, Yandex School of Data Analysis, Higher School of Economics)
19/02/2016, 11:00
Mr
Zachary Chase Lipton
(University of California, Amazon)
19/02/2016, 11:40
Lev Dudko
(M.V. Lomonosov Moscow State University (RU))
19/02/2016, 12:10
Different steps of NN application in HEP are considered. Possible
optimization methods for each of the steps are discussed. The proposed
methods were applied for the single top quark analysis in CMS and
corresponding examples are presented in the talk.
Dr
Joaquin Vanschoren
(https://www.tue.nl)
19/02/2016, 15:00
Dr
Artem Vorozhtsov
(Yandex)
19/02/2016, 16:10
We present a simple approach to test correctness of bias or regularization strength, or other hyperparameters.
The main idea is to fit hyperparameters so that test and train calibration curves after applying proper isotonic regression should intersect at diagonal.
Aleksei Rogozhnikov
(Yandex School of Data Analysis (RU)),
Andrey Ustyuzhanin
(Yandex School of Data Analysis (RU))
19/02/2016, 16:30
Mr
Alexander Fonarev
(Skoltech)
20/02/2016, 09:00
The training process of a machine learning algorithm includes tuning of hyperparameters, such as the regularization coefficient of a linear model or the depth of a decision tree. Unfortunately, it usually is conducted manually, what is very expensive to be done on a regular basis. Moreover, the growing number of hyperparameters in modern complex machine learning methods additionally...
Amir Farbin
(University of Texas at Arlington (US))
20/02/2016, 09:40
Andrey Ustyuzhanin
(Yandex School of Data Analysis (RU))
20/02/2016, 11:20
Rafal Jozefowicz
(Google)
20/02/2016, 12:00
Introduction into deep learning, hands-on tutorial and demonstration of TensorFlow using HiggsML challenge dataset.
Rafal Jozefowicz
(Google)
20/02/2016, 13:30
Andrey Ustyuzhanin
(Yandex School of Data Analysis (RU)),
Marcin Chrzaszcz
(Universitaet Zuerich (CH), Institute of Nuclear Physics (PL))
20/02/2016, 14:50
