Report of Contributions

(1)

Heavy Flavour Data Mining

workshop

Report of Contributions

(2)

Heavy Flavour . . . / Report of Contributions Welcome

Contribution ID :1 Type : not specified

Welcome

Thursday, 18 February 2016 09:00 (10)

Summary

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Heavy Flavour . . . / Report of Contributions Classifiers for centrality determ . . .

Classifiers for centrality determination in

proton-nucleus and nucleus-nucleus collisions

Friday, 19 February 2016 09:40 (20)

Summary

Primary author(s) :

Igor Altsybeev (St. Petersburg State University (RU))

Co-author(s) :

Vladimir Kovalenko (St. Petersburg State University (RU))

Presenter(s) :

Igor Altsybeev (St. Petersburg State University (RU))

Session Classification :

Data Science Applications

(4)

Heavy Flavour . . . / Report of Contributions Summary of «Flavors of Physic . . .

Summary of «Flavors of Physics» Challenge

Summary

Presenter(s) :

Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))

Session Classification :

HEP challenges

(5)

Heavy Flavour . . . / Report of Contributions Classifier output calibration to . . .

Classifier output calibration to probability

Friday, 19 February 2016 09:00 (40)

Summary

Presenter(s) :

Tatiana Likhomanenko (National Research Centre Kurchatov Institute (RU))

Session Classification :

Data Science Applications

(6)

Heavy Flavour . . . / Report of Contributions Data Fusion Surogate Modeling . . .

Data Fusion Surogate Modeling on Incomplete

Factorial Design of Experiments

Friday, 19 February 2016 10:00 (40)

Summary

Presenter(s) :

Eugene Burnaev (IITP)

Session Classification :

Data Science Applications

(7)

Heavy Flavour . . . / Report of Contributions Boosting applications for HEP

Boosting applications for HEP

Summary

Presenter(s) :

Aleksei Rogozhnikov (Yandex School of Data Analysis (RU))

Session Classification :

Machine Learning tools & tutorials

(8)

Heavy Flavour . . . / Report of Contributions An introduction to machine lea . . .

An introduction to machine learning with

Scikit-Learn

Summary

Presenter(s) :

Gilles Louppe (New York University (US))

Session Classification :

Machine Learning tools & tutorials

(9)

Heavy Flavour . . . / Report of Contributions Reproducible Experiment Platf . . .

Reproducible Experiment Platform & Everware

Friday, 19 February 2016 16:30 (120)

Summary

Presenter(s) :

Aleksei Rogozhnikov (Yandex School of Data Analysis (RU))

;

Session Classification :

Machine Learning tools & tutorials

(10)

Heavy Flavour . . . / Report of Contributions Mathematics of Big Data

Mathematics of Big Data

Friday, 19 February 2016 11:00 (40)

Summary

Presenter(s) :

Dmitry Vetrov (Skoltech, Yandex School of Data Analysis, Higher School of Economics)

Session Classification :

Data Science Applications

(11)

Heavy Flavour . . . / Report of Contributions Efficient Elastic Net Regulariza . . .

Efficient Elastic Net Regularization for Sparse Linear

Models in the Multilabel Setting

Friday, 19 February 2016 11:40 (30)

Summary

Presenter(s) :

Zachary Chase Lipton (University of California, Amazon)

Session Classification :

Data Science Applications

(12)

Heavy Flavour . . . / Report of Contributions Data Doping solution for "Flav . . .

Data Doping solution for "Flavours of Physics"

challenge

Summary

Presenter(s) :

Vicens Gaitan

Session Classification :

HEP challenges

(13)

Heavy Flavour . . . / Report of Contributions Transfer Learning solution for . . .

Transfer Learning solution for "Flavours of Physics"

challenge

Summary

Presenter(s) :

Alexander Rakhlin

Session Classification :

HEP challenges

(14)

Heavy Flavour . . . / Report of Contributions OpenML: Collaborative machi . . .

OpenML: Collaborative machine learning

Friday, 19 February 2016 15:00 (40)

Summary

Today, the ubiquity of the internet is allowing new, more scalable forms of scientific col-laboration. Networked science tools allow scientists to share and organize data on a global scale, build directly on each other’s data and techniques, reuse them in unforeseen ways, and mine all data to search for patterns. OpenML.org is a place for researchers to analyse data together, building on shared data sets, machine learning code and prior experiments. Inte-grated in many machine learning environments, it helps researchers win time by automating reproducible sharing, reuse and experimentation as much as possible. It also helps scientists and students across scientific fields to explore the latest and most relevant open data sets and machine learning techniques, find out which are most useful in their work, collaborate with others online, and gain more credit for their work by making it more visible and easily reusable.

Presenter(s) :

Joaquin Vanschoren (https://www.tue.nl)

Session Classification :

Machine Learning tools & tutorials

(15)

Heavy Flavour . . . / Report of Contributions Data Science at LHCb

Data Science at LHCb

Summary

Presenter(s) :

Tim Head (Ecole Polytechnique Federale de Lausanne (CH))

Session Classification :

HEP challenges

(16)

Heavy Flavour . . . / Report of Contributions Closing Remarks

Closing Remarks

Saturday, 20 February 2016 14:50 (10)

Summary

Presenter(s) :

;

Marcin Chrzaszcz (Universitaet Zuerich (CH), Institute of Nuclear Physics (PL))

(17)

Heavy Flavour . . . / Report of Contributions Summary of open space discussions

Summary of open space discussions

Summary

Presenter(s) :

Session Classification :

Data Science Applications

(18)

Heavy Flavour . . . / Report of Contributions TensorFlow introduction & tut . . .

TensorFlow introduction & tutorial #1

Summary

Primary author(s) :

Rafal Jozefowicz (Google)

Presenter(s) :

Session Classification :

Machine Learning tools & tutorials

(19)

Heavy Flavour . . . / Report of Contributions Pitfalls of evaluating a classifie . . .

Pitfalls of evaluating a classifier’s performance in

high energy physics applications

Summary

Presenter(s) :

Gilles Louppe (New York University (US))

Session Classification :

HEP challenges

(20)

Heavy Flavour . . . / Report of Contributions Optimized Methods to Apply . . .

Optimized Methods to Apply Neural Networks in

HEP

Friday, 19 February 2016 12:10 (20)

Summary

Primary author(s) :

Lev Dudko (M.V. Lomonosov Moscow State University (RU))

Presenter(s) :

Lev Dudko (M.V. Lomonosov Moscow State University (RU))

Session Classification :

Data Science Applications

(21)

Heavy Flavour . . . / Report of Contributions Automatic Tuning of Hyperpar . . .

Automatic Tuning of Hyperparameters

Summary

Primary author(s) :

Alexander Fonarev (Skoltech)

Presenter(s) :

Alexander Fonarev (Skoltech)

Session Classification :

Data Science Applications

(22)

Heavy Flavour . . . / Report of Contributions Calibration curves as tool to te . . .

Calibration curves as tool to test for over- and

underfitting

Friday, 19 February 2016 16:10 (20)

Summary

Primary author(s) :

Artem Vorozhtsov (Yandex)

Presenter(s) :

Artem Vorozhtsov (Yandex)

Session Classification :

Machine Learning tools & tutorials

(23)

Heavy Flavour . . . / Report of Contributions Fast multimodal clustering: se . . .

Fast multimodal clustering: searching for optimal

patterns

Summary

Primary author(s) :

Dmitry Ignatov (HSE)

Presenter(s) :

Dmitry Ignatov (HSE)

Session Classification :

Data Science Applications

(24)

Heavy Flavour . . . / Report of Contributions Deep Learning for event recons . . .

Deep Learning for event reconstruction

Summary

Presenter(s) :

Amir Farbin (University of Texas at Arlington (US))

Session Classification :

Data Science Applications

(25)

Heavy Flavour . . . / Report of Contributions TensorFlow introduction & tut . . .