Publications associées à Ancillary statistic

Testing For The Rank Of A Covariance Operator

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

Pollution Detection Algorithm (PDA)

Julia Schmale, Andrea Baccarini, Ivo Fabio Beck, Hélène Paule Angot

The Pollution Detection Algorithm (PDA) is an algorithm to identify and flag periods of primary polluted data in remote atmospheric time series in five steps. The first and most important step identifies polluted periods based on the gradient (time-derivat ...

Zenodo2021

A Pareto Dominance Principle for Data-Driven Optimization

Daniel Kuhn, Tobias Sutter

We propose a statistically optimal approach to construct data-driven decisions for stochastic optimization problems. Fundamentally, a data-driven decision is simply a function that maps the available training data to a feasible action. It can always be exp ...

2024

Testing general relativity on cosmological scales at redshift z similar to 1.5 with quasar and CMB lensing

Cheng Zhao

We test general relativity (GR) at the effective redshift (z) over tilde similar to 1.5 by estimating the statistic E-G, a probe of gravity, on cosmological scales 19 - 190 h(-1)Mpc. This is the highest redshift and largest scale estimation of E-G so far. ...

OXFORD UNIV PRESS2021

Concept Discovery for The Interpretation of Landscape Scenicness

Devis Tuia

In this paper, we study how to extract visual concepts to understand landscape scenicness. Using visual feature representations from a Convolutional Neural Network (CNN), we learn a number of Concept Activation Vectors (CAV) aligned with semantic concepts ...

2020

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

ChoiceRank: Identifying Preferences from Node Traffic in Networks

Matthias Grossglauser, Lucas Maystre

Understanding how users navigate in a network is of high interest in many applications. We consider a setting where only aggregate node-level traffic is observed and tackle the task of learning edge transition probabilities. We cast it as a preference lear ...

2017

Equivalent electricity storage capacity of domestic thermostatically controlled loads

Fabrizio Sossan

A method to quantify the equivalent storage capacity inherent the operation of thermostatically controlled loads (TCLs) is developed. Equivalent storage capacity is defined as the amount of power and electricity consumption which can be deferred or anticip ...

Pergamon-Elsevier Science Ltd2017

Deep neural network based posteriors for text-dependent speaker verification

Petr Motlicek, Subhadeep Dey

The i-vector and Joint Factor Analysis (JFA) systems for text- dependent speaker verification use sufficient statistics computed from a speech utterance to estimate speaker models. These statis- tics average the acoustic information over the utterance ther ...

IEEE2016

Statistical methods for comparing brain connectomes at different scales

Dimitri Nestor Alice Van De Ville, Stephan Morgenthaler, Djalel Eddine Meskaldji

Physiological Brain connectivity and spontaneous interaction between regions of interest of the brain can be represented by a matrix (full or sparse) or equivalently by a complex network called connectome. This representation of brain connectivity is adopt ...

SPIE-Int Soc Optical Engineering2015

In vivo evaluation of a novel 'diastole-patching' algorithm for the estimation of pulse transit time: advancing the precision in pulse wave velocity measurement

Nikolaos Stergiopoulos, Orestis Vardoulis

Carotid-to-femoral pulse wave velocity (PWV) is the gold standard for the assessment of aortic stiffness. It is calculated by the ratio of pulse transit time (PTT) between two arterial sites and the distance between them. The precision of PTT estimation de ...

Institute of Physics2015

Sparsity-Driven Statistical Inference for Inverse Problems

Ulugbek Kamilov

This thesis addresses statistical inference for the resolution of inverse problems. Our work is motivated by the recent trend whereby classical linear methods are being replaced by nonlinear alternatives that rely on the sparsity of naturally occurring sig ...

EPFL2015

Population Sensing Using Mobile Devices : a Statistical Opportunity or a Privacy Nightmare?

Farid Movahedi Naini

In our daily lives, our mobile phones sense our movements and interactions via a rich set of embedded sensors such as a GPS, Bluetooth, accelerometers, and microphones. This enables us to use mobile phones as agents for collecting spatio-temporal data. The ...

EPFL2014

A FFINITY: Efficiently Querying Statistical Measures on Time-Series Data

Karl Aberer, Saket Sathe

Computing statistical measures for large databases of time series is a fundamental primitive for querying and mining time-series data [1]–[6]. This primitive is gaining importance with the increasing number and rapid growth of time series databases. In thi ...

IEEE2013

Statistical Models for Querying and Managing Time-Series Data

Saket Sathe

In recent years we are experiencing a dramatic increase in the amount of available time-series data. Primary sources of time-series data are sensor networks, medical monitoring, financial applications, news feeds and social networking applications. Availab ...

EPFL2013

Development of a standard fall data format for signals from body-worn sensors The FARSEEING consensus

Kamiar Aminian

Objective measurement of real-world fall events by using body-worn sensor devices can improve the understanding of falls in older people and enable new technology to prevent, predict, and automatically recognize falls. However, these events are rare and he ...

Springer Heidelberg2013

Drift Correction in Multivariate Calibration Models Using On-line Reference Measurements

Dominique Bonvin, Michael Amrhein, Pamandeep Singh Gujral

On-line measurements from first-order instruments such as spectrometers may be compromised by instrumental, process and operational drifts that are not seen during off-line calibration. This can render the calibration model unsuitable for prediction of key ...

2009

Conditionally least-informative distributions: The case of the location parameter

Stephan Morgenthaler

We extend a basic result of Huber's on least favorable distributions to the setting of conditional inference, using an approach based on the notion of log-Gâteaux differentiation and perturbed models. Whereas Huber considered intervals of fixed width for l ...

2005