Concept

Régression multivariée par spline adaptative

Publications associées (94)

The SDSS-IV eBOSS: emission line galaxy catalogues at z approximate to 0.8 and study of systematic errors in the angular clustering

Jean-Paul Richard Kneib, Johan Comparat, Xiaoqing Zhou, Anand Stéphane Raichoor, Timothée Guy Olivier Delubac

We present two wide-field catalogues of photometrically selected emission line galaxies (ELGs) at z approximate to 0.8 covering about 2800 deg(2)over the south galactic cap. The catalogues were obtained using a Fisher discriminant technique described in a ...

Oxford Univ Press2017

Mitigating the impact of errors in travel time reporting on mode choice modelling

Michel Bierlaire, Aurélie Glerum, Giovanni Longo, Amanda Blomberg Stathopoulos, Silvia Francesca Varotto

Travel time is a major component in understanding travel demand. However, the quantification of demand and forecasting hinges on understanding how travel time is perceived and reported. Travel time reporting is typically subject to errors and this paper fo ...

Elsevier Sci Ltd2017

The impact of flood variables on riparian vegetation

Katarína Dzubáková, Peter Molnar

The riparian vegetation of Alpine rivers often grows in temporally dynamic riverine environments which are characterized by pronounced meteorological and hydrological fluctuations and high resource competition. Within these relatively rough conditions, rip ...

2016

Fluctuations of spontaneous EEG topographies predict disease state in relapsing-remitting multiple sclerosis

Dimitri Nestor Alice Van De Ville

Spontaneous fluctuations of neuronal activity in large-scale distributed networks are a hallmark of the resting brain. In relapsing-remitting multiple sclerosis (RRMS) several fMRI studies have suggested altered resting-state connectivity patterns. Topogra ...

Elsevier Sci Ltd2016

Predicting Individual Scores From Resting State fMRI Using Partial Least Squares Regression

Dimitri Nestor Alice Van De Ville, Stephan Morgenthaler, Thomas William Arthur Bolton, Maria Giulia Preti, Djalel Eddine Meskaldji

An important question in neuroscience is to reveal the relationship between individual performance and brain activity. This could be achieved by applying model regression techniques, in which functional connectivity derived from resting-state functional ma ...

Ieee2016

Efficient Distributed Decision Trees for Robust Regression

Karl Aberer, Jean Paul Calbimonte Perez, Tian Guo

The availability of massive volumes of data and recent advances in data collection and processing platforms have motivated the development of distributed machine learning algorithms. In numerous real-world applications large datasets are inevitably noisy a ...

2016

Regression Analysis of Building Energy Demand

This project attempts to tackle the problem of analysing the heat demand of build- ings at a large (district or city) scale. Specifically, building data from Geneva is used as a case study while building an environment with suitable tools for a continued a ...

2015

Blood flow velocity field estimation via spatial regression with PDE penalization

Fabio Nobile

We propose an innovative method for the accurate estimation of surfaces and spatial fields when prior knowledge of the phenomenon under study is available. The prior knowledge included in the model derives from physics, physiology, or mechanics of the prob ...

American Statistical Association2015

Comparison of the two point bending and four point bending test methods for aged asphalt concrete field samples

André-Gilles Dumont, Michel Pittet, Manfred Partl

Complex modulus and fatigue behavior are important characteristics for all materials. Some European countries have developed performance oriented requirements for bituminous mixtures. Using such requirements it is expected that the life of pavements can be ...

Springer Verlag2015

From averaging to acceleration, there is only a step-size

Nicolas Henri Bernard Flammarion

We consider the optimization of a quadratic objective function whose gradients are only accessible through a stochastic oracle that returns the gradient at any given point plus a zero-mean finite variance random error. We present the first algorithm that a ...

2015

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