Heavy Flavour Data Mining workshop

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Sessions*

Machine Learning tools & tutorials

HEP challenges

HEP challenges discussions

Data Science Applications

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Contributions*

An introduction to machine learning with Scikit-Learn (in session "Machine Learning tools & tutorials")

Automatic Tuning of Hyperparameters (in session "Data Science Applications")

Boosting applications for HEP (in session "Machine Learning tools & tutorials")

Calibration curves as tool to test for over- and underfitting (in session "Machine Learning tools & tutorials")

Classifier output calibration to probability (in session "Data Science Applications")

Classifiers for centrality determination in proton-nucleus and nucleus-nucleus collisions (in session "Data Science Applications")

Closing Remarks

Data Doping solution for "Flavours of Physics" challenge (in session "HEP challenges")

Data Fusion Surogate Modeling on Incomplete Factorial Design of Experiments (in session "Data Science Applications")

Data Science at LHCb (in session "HEP challenges")

Deep Learning for event reconstruction (in session "Data Science Applications")

Efficient Elastic Net Regularization for Sparse Linear Models in the Multilabel Setting (in session "Data Science Applications")

Fast multimodal clustering: searching for optimal patterns (in session "Data Science Applications")

Mathematics of Big Data (in session "Data Science Applications")

Nvidia tutorial (in session "Machine Learning tools & tutorials")

OpenML: Collaborative machine learning (in session "Machine Learning tools & tutorials")

Optimized Methods to Apply Neural Networks in HEP (in session "Data Science Applications")

Pitfalls of evaluating a classifier's performance in high energy physics applications (in session "HEP challenges")

Reproducible Experiment Platform & Everware (in session "Machine Learning tools & tutorials")

Summary of open space discussions (in session "Data Science Applications")

Summary of «Flavors of Physics» Challenge (in session "HEP challenges")

TensorFlow introduction & tutorial #1 (in session "Machine Learning tools & tutorials")

TensorFlow introduction & tutorial. Continuation (in session "Machine Learning tools & tutorials")

Transfer Learning solution for "Flavours of Physics" challenge (in session "HEP challenges")

Welcome

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Events scheduled on*

18/02/2016

19/02/2016

20/02/2016

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