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08:00
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Registration
(until 08:15)
()
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08:15
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--- breakfast ---
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09:00
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Welcome
-
Andrey Ustyuzhanin
(Yandex School of Data Analysis (RU))
(until 09:35)
(204)
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09:00
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Welcome to MLHEP
(204)
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09:20
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MLHEP Kaggle competition
-
Nikita Kazeev
(Yandex School of Data Analysis (RU))
(204)
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09:35
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--- break ---
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09:40
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Advanced track
-Dr
Victor Kitov
(MSU)
(until 12:40)
(206)
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09:40
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Reminder about major algorithms. Advanced aspects of their use. Model evaluation.
(206)
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11:00
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--- coffee break ---
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11:20
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Feature selection. Regularization.
(206)
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09:40
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Introductory track
-
Alexey Rogozhnikov
(until 12:40)
(204)
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09:40
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Intro: General pipeline, ML at a glance
(204)
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11:00
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--- coffee break ---
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11:20
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Intro: kNN, basic overfitting, roc curve, logistic regression
(204)
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08:15
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--- breakfast ---
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09:30
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Advanced track
-Dr
Victor Kitov
(MSU)
(until 12:30)
(206)
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09:30
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model ensembling #1
(206)
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10:50
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--- coffee break ---
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11:10
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model ensembling #2
(206)
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09:30
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Introductory track
-
Alexey Rogozhnikov
(until 12:30)
(204)
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09:30
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neural networks
(204)
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10:50
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--- coffee break ---
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11:10
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decision tree, regression tree
(204)
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08:15
|
--- breakfast ---
|
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09:30
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Advanced track
-Dr
Victor Kitov
(MSU)
(until 12:30)
(206)
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09:30
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Linear dimensionality reduction.
(206)
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10:50
|
--- coffee break ---
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11:10
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Non-linear dimensionality reduction. Kernel trick. Common kernels.
(206)
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09:30
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Introductory track
-
Alexey Rogozhnikov
(until 12:30)
(204)
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09:30
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Ensembles
(204)
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10:50
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--- coffee break ---
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11:10
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Gradient boosting; boosting to uniformity.
(204)
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08:15
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--- breakfast ---
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09:00
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Advanced track
-Dr
Victor Kitov
(MSU)
(until 12:00)
(206)
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09:00
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Kernelized algorithms: SVM, regression, K-NN, PCA and their properties.
(206)
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10:20
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--- coffee break ---
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10:40
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Deep learning. Different kinds of learning.
(206)
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09:00
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Introductory track
-
Alexey Rogozhnikov
(until 12:00)
(204)
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09:00
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GBDT tuning, reweighting, testing hypotheses, gaussian processes for optimization
(204)
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10:20
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--- coffee break ---
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10:40
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Unsupervised learning, Latent Dirichlet Allocation, PCA. Fast predictions and pruning
(204)
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12:40
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--- lunch ---
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13:45
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Advanced track
-
Tatiana Likhomanenko
(National Research Centre Kurchatov Institute (RU))
(until 17:10)
(206)
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13:45
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MLHEP introduction. ML vs MLHEP: correlation and agreement restrictions
-
Tatiana Likhomanenko
(National Research Centre Kurchatov Institute (RU))
(206)
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15:15
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--- coffee break ---
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15:40
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sPlot technique. ML on sPlot data.
(206)
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13:45
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Introductory track
-
Nikita Kazeev
(Yandex School of Data Analysis (RU))
(until 17:10)
(204)
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13:45
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Introduction, course technicalities
(204)
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15:15
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--- coffee break ---
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15:40
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NumPy, Pandas, Matplotlib
(204)
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17:10
|
--- break ---
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17:20
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Applying Machine Learning to LHC triggers optimization
-
Mika Anton Vesterinen
(Ruprecht-Karls-Universitaet Heidelberg (DE))
(204)
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19:00
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--- Welcome dinner ---
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12:30
|
--- lunch ---
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13:45
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Advanced track
-
Tatiana Likhomanenko
(National Research Centre Kurchatov Institute (RU))
(until 17:10)
(206)
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13:45
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Brave new boosting world: flatness boosting
(206)
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15:15
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--- coffee break ---
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15:40
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Brave new boosting world: reweighing boosting. Iterative learning
(206)
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13:45
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Introductory track
-
Nikita Kazeev
(Yandex School of Data Analysis (RU))
(until 17:10)
(204)
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13:45
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Overfitting, Cross-validation
(204)
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15:15
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--- coffee break ---
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15:40
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Sklearn: KNN, decision tree, logistic regression
(204)
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17:10
|
--- break ---
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17:30
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Challenges of searching for physics signatures with a large amount of background
-
Patrick Haworth Owen
(Imperial College Sci., Tech. & Med. (GB))
(204)
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12:30
|
--- lunch ---
|
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13:45
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Advanced track
-
Tatiana Likhomanenko
(National Research Centre Kurchatov Institute (RU))
(until 17:10)
(206)
|
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13:45
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Meta Algorithms Applications in HEP.
(206)
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15:15
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--- coffee break ---
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15:40
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Hypotheses testing.
(206)
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13:45
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Introductory track
-
Nikita Kazeev
(Yandex School of Data Analysis (RU))
(until 17:10)
(204)
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13:45
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Ensemble algorithms: random forest, gradient boosting
(204)
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15:15
|
--- coffee break ---
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15:40
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Hyperparam Optimization
(204)
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17:10
|
--- break ---
|
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17:30
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MVA vs cut-and-count techniques in the SM model processes searches and measurements
-
Lesya Shchutska
(University of Florida (US))
(204)
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12:00
|
--- lunch ---
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13:00
|
Advanced track
-
Tatiana Likhomanenko
(National Research Centre Kurchatov Institute (RU))
(until 16:15)
(206)
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13:00
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Summary: HEP ML analysis sketch, from data to discovery.
(206)
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14:30
|
--- coffee break ---
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14:45
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My own first NN using theano.
(206)
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13:00
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Introductory track
-
Nikita Kazeev
(Yandex School of Data Analysis (RU))
(until 16:15)
(204)
|
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13:00
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PCA, RBM and alike on MNIST
(204)
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14:30
|
--- coffee break ---
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14:45
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Clustering
(204)
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16:15
|
--- break ---
|
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16:20
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Multivariate techniques in the Higgs search
-
Josh Bendavid
(CERN)
(204)
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18:00
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--- transfer to the boat ---
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19:00
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--- channel cruise + closing dinner + awards ---
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22:00
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--- transfer to the hotel ---
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