Myrto Limnios

myrto.limnios@epfl.ch +41 21 693 01 89 https://myrtolimnios.github.io

+41 21 693 01 89
EPFL > SB > SB-SMA > SMA-ENS

Web site:  Web site:  https://sma.epfl.ch/

EPFL SB MATH
CM 1 618 (Centre Midi)
Station 10
1015 Lausanne

+41 21 693 01 89
Office:  CM 1 618
EPFL > SB > MATH > MATH-GE

Web site:  Web site:  https://math.epfl.ch/

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Administrative data

Teaching & PhD

Teaching

Mathematics

Courses

Regression methods

Linear regression and analysis of variance. Geometric interpretation.  Properties of estimators.  Orthogonality and balance.  Diagnostics.  Transformations.  Variable selection and post-selection inference.  Robustness and estimating equations.  Quantile regression. PIWLS algorithm and general regression models. Generalized linear models; logistic regession; count data and Poisson respon

Empirical processes

We learn how to control the nonasymptotic and random behavior of collections of estimators, when indexed by classes of functions/sets. Examples range from prototypical estimators used by statisticians, to nonparametric models used in machine learning.