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Concept

False discovery rate

Related publications (28)

Data-Driven Chance Constrained Programs over Wasserstein Balls

Daniel Kuhn, Wolfram Wiesemann

We provide an exact deterministic reformulation for data-driven chance constrained programs over Wasserstein balls. For individual chance constraints as well as joint chance constraints with right-hand side uncertainty, our reformulation amounts to a mixed ...

2024

Density estimation in RKHS with application to Korobov spaces in high dimensions

Fabio Nobile, Yoshihito Kazashi

A kernel method for estimating a probability density function from an independent and identically distributed sample drawn from such density is presented. Our estimator is a linear combination of kernel functions, the coefficients of which are determined b ...

2023

Evaluation and optimization of novel extraction algorithms for the automatic detection of atrial activations recorded within the pulmonary veins during atrial fibrillation

Jean-Marc Vesin, Etienne Pruvot, Sasan Yazdani, Adrian Luca, Yann Prudat

Background and objective The automated detection of atrial activations (AAs) recorded from intracardiac electrograms (IEGMs) during atrial fibrillation (AF) is challenging considering their various amplitudes, morphologies and cycle length. Activation time ...

BMC2022

Social Learning with Disparate Hypotheses

Ali H. Sayed, Stefan Vlaski, Virginia Bordignon, Konstantinos Ntemos

In this paper we study the problem of social learning under multiple true hypotheses and self-interested agents. In this setup, each agent receives data that might be generated from a different hypothesis (or state) than the data other agents receive. In c ...

IEEE2022

Testing For The Rank Of A Covariance Operator

Victor Panaretos

How can we discern whether the covariance operator of a stochastic pro-cess is of reduced rank, and if so, what its precise rank is? And how can we do so at a given level of confidence? This question is central to a great deal of methods for functional dat ...

INST MATHEMATICAL STATISTICS-IMS2022

Smart pooling: AI-powered COVID-19 informative group testing

Jorge Andres Madrid Wolff

Massive molecular testing for COVID-19 has been pointed out as fundamental to moderate the spread of the pandemic. Pooling methods can enhance testing efficiency, but they are viable only at low incidences of the disease. We propose Smart Pooling, a machin ...

Nature Portfolio2022

Cortical and subcortical changes in resting-state neuronal activity and connectivity in early symptomatic ALS and advanced frontotemporal dementia

Alessandra Griffa

The objective of this study was to examine if patterns of resting-state brain activity and functional connectivity in cortical and subcortical regions in patients with early symptomatic amyotrophic lateral sclerosis (ALS) resemble those of behavioural vari ...

ELSEVIER SCI LTD2022

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

Differentiation between benign and malignant vertebral compression fractures using qualitative and quantitative analysis of a single fast spin echo T2-weighted Dixon sequence

Tom Hilbert

Objectives To determine and compare the qualitative and quantitative diagnostic performance of a single sagittal fast spin echo (FSE) T2-weighted Dixon sequence in differentiating benign and malignant vertebral compression fractures (VCF), using multiple r ...

SPRINGER2021

FANOK: Knockoffs in Linear Time

Quentin Rebjock

We describe a series of algorithms that efficiently implement Gaussian model-X knockoffs to control the false discovery rate on large-scale feature selection problems. Identifying the knockoff distribution requires solving a large-scale semidefinite progra ...

SIAM PUBLICATIONS2021

Wastewater monitoring outperforms case numbers as a tool to track COVID-19 incidence dynamics when test positivity rates are high

Tamar Kohn, Timothy R. Julian, Joseph Chadi Benoit Lemaitre, Xavier Fernandez Cassi, Alex Tunas Corzon, Federica Cariti

Wastewater-based epidemiology (WBE) has been shown to coincide with, or anticipate, confirmed COVID-19 case numbers. During periods with high test positivity rates, however, case numbers may be underreported, whereas wastewater does not suffer from this li ...

2021

Confronting false discoveries in single-cell differential expression

Grégoire Courtine, Gioele La Manno, Quentin Barraud, Jordan Squair, Matthieu Pierre Gautier, Mark Andrew Anderson, Nicholas David James, Thomas Haynes Hutson, Claudia Kathe, Michael Alexander Skinnider, Rémi Bernard René Hudelle

Differential expression analysis of single-cell transcriptomics allows scientists to dissect cell-type-specific responses to biological perturbations. Here, the authors show that many commonly used methods are biased and can produce false discoveries. ...

Nature Portfolio2021

Interpreting null models of resting-state functional MRI dynamics: not throwing the model out with the hypothesis

Dimitri Nestor Alice Van De Ville, Raphaël Pierre Liégeois

Null models are useful for assessing whether a dataset exhibits a non-trivial property of interest. These models have recently gained interest in the neuroimaging community as means to explore dynamic properties of functional Magnetic Resonance Imaging (fM ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2021

Sampling strategy optimization to increase statistical power in landscape genomics: a simulation-based approach

Stéphane Joost, Estelle Rochat, Oliver Michele Selmoni, Elia Vajana, Annie Sandrine Guillaume

An increasing number of studies are using landscape genomics to investigate local adaptation in wild and domestic populations. The implementation of this approach requires the sampling phase to consider the complexity of environmental settings and the burd ...

2020

Learning and Adaptive Data Analysis via Maximal Leakage

Michael Christoph Gastpar, Amedeo Roberto Esposito, Ibrahim Issa

There has been growing interest in studying connections between generalization error of learning algorithms and information measures. In this work, we generalize a result that employs the maximal leakage, a measure of leakage of information, and explore ho ...

IEEE2019

Longitudinal analysis of white matter and cortical lesions in multiple sclerosis

Tobias Kober, Meritxell Bach Cuadra, Cristina Granziera

Purpose: The goals of this study were to assess the performance of a novel lesion segmentation tool for longitudinal analyses, as well as to validate the generated lesion progression map between two time points using conventional and non-conventional MR se ...

2019

Advantages of fluid and white matter suppression (FLAWS) with MP2RAGE compared with double inversion recovery turbo spin echo (DIR-TSE) at 7T

Tobias Kober

Cerebrospinal fluid (CSF) and white matter (WM) signal suppression techniques allow better visualization of both WM and gray matter (GM) lesions in such disorders as multiple sclerosis and epilepsy. Recently, a technique, FLuid And White matter Suppression ...

ELSEVIER IRELAND LTD2019

Statistical Applications of Random Matrix Theory: Comparison of Two Populations

Rémy Mariétan

During the last twenty years, Random matrix theory (RMT) has produced numerous results that allow a better understanding of large random matrices. These advances have enabled interesting applications in the domain of communication. Although this theory can ...

EPFL2019

High-Contrast Imaging of Nanodiamonds in Cells by Energy Filtered and Correlative Light-Electron Microscopy: Toward a Quantitative Nanoparticle-Cell Analysis

Theo Lasser

Fluorescent nanodiamonds (fNDs) represent an emerging class of nanomaterials offering great opportunities for ultrahigh resolution imaging, sensing and drug delivery applications. Their biocompatibility, exceptional chemical and consistent photostability r ...

2019

Adaptive Design of Experiments for Conservative Estimation of Excursion Sets

We consider the problem of estimating the set of all inputs that leads a system to some particular behavior. The system is modeled by an expensive-to-evaluate function, such as a computer experiment, and we are interested in its excursion set, that is, the ...

2021