Institutsseminar/2021-11-12 ZusatzIPD

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Termin (Alle Termine)
Datum Fr 12. November 2021, 11:30 Uhr
Dauer 20 min
Vorheriger Termin Fr 5. November 2021
Nächster Termin Fr 12. November 2021


Vortragende(r) Li Mingyi
Titel On the Converge of Monte Carlo Dependency Estimators
Vortragstyp Proposal
Betreuer(in) Edouard Fouché
Kurzfassung Estimating dependency is essential for data analysis. For example in biological analysis, knowing the correlation between groups of proteins and genes may help predict genes functions, which makes cure discovery easier.

The recently introduced Monte Carlo Dependency Estimation (MCDE) framework defines the dependency between a set of variables as the expected value of a stochastic process performed on them. In practice, this expected value is approximated with an estimator which iteratively performs a set of Monte Carlo simulations. In this thesis, we propose several alternative estimators to approximate this expected value. They function in a more dynamic way and also leverage information from previous approximation iterations. Using both probability theory and experiments, we show that our new estimators converge much faster than the original one.

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