Publications associées à Test du multiplicateur de Lagrange

Generalized Bradley-Terry Models for Score Estimation from Paired Comparisons

Sadegh Farhadkhani, Oscar Jean Olivier Villemaud, Julien René Pierre Fageot, Le Nguyen Hoang

Many applications, e.g. in content recommendation, sports, or recruitment, leverage the comparisons of alternatives to score those alternatives. The classical Bradley-Terry model and its variants have been widely used to do so. The historical model conside ...

AAAI Press2024

Transportation-based functional ANOVA and PCA for covariance operators

Victor Panaretos, Yoav Zemel, Valentina Masarotto

We consider the problem of comparing several samples of stochastic processes with respect to their second-order structure, and describing the main modes of variation in this second order structure, if present. These tasks can be seen as an Analysis of Vari ...

Inst Mathematical Statistics-Ims2024

Removing Algorithmic Discrimination (With Minimal Individual Error)

Rachid Guerraoui, El Mahdi El Mhamdi, Alexandre David Olivier Maurer, Le Nguyen Hoang

We address for the first time the problem of correcting group discriminations within a score function, while minimizing the individual error. Each group is described by a probability density function on the set of profiles. We first solve the problem analy ...

2022

Estimation of Charge Transfer During Long Continuing Currents in Natural Downward Flashes Using Single‐Station E‐Field Measurements

Farhad Rachidi-Haeri, Wolfgang Schulz, Hannes Kohlmann

The amount of charge transferred to ground during long continuing currents in natural downward flashes can be obtained either through direct current measurements or using remote electromagnetic fields, if direct measurements are not feasible. In this study ...

2022

List Ordered Statistics Decoders for Polar Codes

Andreas Peter Burg, Yifei Shen, Chuan Zhang

The de-facto standard decoding algorithm for polar codes, successive cancellation list (SCL) decoding, is a breadth-first search algorithm. By keeping a list of candidate codewords, SCL decoding improves the performance as the list size L increases. Howeve ...

IEEE2022

Improved Inference On Risk Measures For Univariate Extremes

Anthony Christopher Davison, Léo Raymond-Belzile

We discuss the use of likelihood asymptotics for inference on risk measures in univariate extreme value problems, focusing on estimation of high quantiles and similar summaries of risk for uncertainty quantification. We study whether higher-order approxima ...

INST MATHEMATICAL STATISTICS-IMS2022

Experimental characterisation of textile compaction response: A benchmark exercise

Véronique Michaud, Baris Çaglar, Christophe Lopez

This paper reports the results of an international benchmark exercise on the measurement of fibre bed compaction behaviour. The aim was to identify aspects of the test method critical to obtain reliable results and to arrive at a recommended test procedure ...

2021

Multiple testing with test statistics following heavy-tailed distributions

Zhiwen Jiang

In multiple testing problems where the components come from a mixture model of noise and true effect, we seek to first test for the existence of the non-zero components, and then identify the true alternatives under a fixed significance level

\alpha

. Two ...

EPFL2021

NovelT2Mapping for Evaluating Cervical Cancer Features by Providing QuantitativeT2Maps and Synthetic Morphologic Images: A Preliminary Study

Tobias Kober, Tom Hilbert, Yong Zhang, Meng Yang, Jie Liu

Background The application value of T(2)mapping in evaluating cervical cancer (CC) features remains unclear. Purpose To investigate the role of T(2)values in evaluating CC classification, grade, and lymphovascular space invasion (LVSI) in comparison to app ...

WILEY2020

Learning new physics from a machine

Raffaele Tito D'Agnolo, Andrea Wulzer

We propose using neural networks to detect data departures from a given reference model, with no prior bias on the nature of the new physics responsible for the discrepancy. The virtues of neural networks as unbiased function approximants make them particu ...

American Physical Society2019

Procrustes Metrics and Optimal Transport for Covariance Operators

Valentina Masarotto

Covariance operators play a fundamental role in functional data analysis, providing the canonical means to analyse functional variation via the celebrated Karhunen-Loève expansion. These operators may themselves be subject to variation, for instance in con ...

EPFL2019

High-dimensional peaks-over-threshold inference

Anthony Christopher Davison, Raphaël Gérard Théodore Michel Marie de Deloÿe et Fourcade de Fondeville

Max-stable processes are increasingly widely used for modelling complex extreme events, but existing fitting methods are computationally demanding, limiting applications to a few dozen variables. r-Pareto processes are mathematically simpler and have the p ...

2018

The detection of two-component mixture alternatives : Theory and methods

Daria Rukina

In this thesis, we deal with one of the facets of the statistical detection problem. We study a particular type of alternative, the mixture model. We consider testing where the null hypothesis corresponds to the absence of a signal, represented by some kno ...

EPFL2018

Indicators of Evidence for Bioequivalence

Stephan Morgenthaler, Robert Staudte

Some equivalence tests are based on two one-sided tests, where in many applications the test statistics are approximately normal. We define and find evidence for equivalence in Z-tests and then one-and two-sample binomial tests as well as for t-tests. Mult ...

Mdpi Ag2016

Likelihood estimators for multivariate extremes

Anthony Christopher Davison, Raphaël Huser

The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high t ...

Springer2016

Novel Readout Circuit for Memristive Biosensors in Cancer Detection

Giovanni De Micheli, Sandro Carrara, Francesca Puppo, Ali Zaher

We present a novel circuit for the automated and quick characterization of an array of experimental memristive nanowires that are functionalized as biosensors. Successfully functionalized nanowires will express the concentration of target molecules by hyst ...

IEEE2014

Comparing connectomes across subjects and populations at different scales

Jean-Philippe Thiran, Stephan Morgenthaler, Alessandra Griffa, Elda Fischi Gomez, Patric Hagmann, Djalel Eddine Meskaldji

Brain connectivity can be represented by a network that enables the comparison of the different patterns of struc- tural and functional connectivity among individuals. In the literature, two levels ofstatistical analysis have been con- sidered in comparing ...

2013

From pointwise testing to a regional vision: An integrated statistical approach to detect nonstationarity in extreme daily rainfall. Application to the Sahelian region

Juliette Ferial Blanchet

Global warming is expected to intensify the hydrologic cycle. Documenting whether significant changes in the extreme precipitation regimes have already happened is consequently one of the challenging topics in climatic research. The high natural variabilit ...

Wiley-Blackwell2013

Determination of the X(3872) Meson Quantum Numbers

Olivier Schneider, Aurelio Bay, Yiming Li, Guido Haefeli, Frédéric Blanc, Christoph Frei, Tatsuya Nakada, Julien Rouvinet, Barinjaka Rakotomiaramanana, Raluca Anca Muresan, Michel De Cian, Christophe Salzmann, Johan Luisier, Anne Keune, Jian Wang, Vincent Fave, Yi Zhang, Lei Zhang, Jessica Prisciandaro, Mark Tobin, Minh Tâm Tran, Niko Neufeld, Matthew Needham, Marc-Olivier Bettler, Greig Alan Cowan, Maurizio Martinelli, Vladislav Balagura, Donal Patrick Hill, Cédric Potterat, Jean Wicht, Ilya Komarov, Plamen Hristov Hopchev, Bastien Luca Muster, Frédéric Guillaume Dupertuis, Pierre Jaton, Joël Bressieux, Songmei Wu, Albert Puig Navarro, Hans Dijkstra, Gerhard Raven, Peter Clarke, Frédéric Teubert, , , ,

On Optimal Two Sample Homogeneity Tests for Finite Alphabets

Jayakrishnan Unnikrishnan

Suppose we are given two independent strings of data from a known finite alphabet. We are interested in testing the null hypothesis that both the strings were drawn from the same distribution, assuming that the samples within each string are mutually indep ...

Ieee2012