Binary regression

Publications associées (26)

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A general framework for the integration of complex choice models into mixed integer optimization

Meritxell Pacheco Paneque

The objective of this thesis is to develop a general methodology to incorporate a disaggregate demand representation in supply-oriented optimization problems that allows to capture the interplay between the behavior of individuals and the decisions to be o ...

EPFL2020

Enhancing discrete choice models with representation learning

Alexandre Massoud Alahi, Virginie Janine Camille Lurkin

In discrete choice modeling (DCM), model misspecifications may lead to limited predictability and biased parameter estimates. In this paper, we propose a new approach for estimating choice models in which we divide the systematic part of the utility specif ...

2020

Topology design of general tensegrity with rigid bodies

Yafeng Wang

This study presents a general approach to the topology design of tensegrities with rigid bodies. To the best of the authors' knowledge, all existing topology design methods of tensegrities focus on tensegrities that only consist of members carrying axial f ...

2020

Artificial neural networks can be used for Ambrosia pollen emission parameterization in COSMO-ART

Charlotte Marie Bürki

The emission parameterization is a crucial part of numerical pollen dispersion models. This paper shows that Artificial Neural Networks (ANNs) can substantially improve the performance of the Ambrosia pollen emission in numerical pollen dispersion models s ...

Elsevier2019

On Certifying Non-Uniform Bounds against Adversarial Attacks

Volkan Cevher, Chen Liu

This work studies the robustness certification problem of neural network models, which aims to find certified adversary-free regions as large as possible around data points. In contrast to the existing approaches that seek regions bounded uniformly along a ...

2019

Professional cyclic high mobility: modelling state transitions

Michel Bierlaire, Vincent Kaufmann, Emmanuel Pierre Jean Ravalet, Alexis Gumy, Matthieu Marie Cochon de Lapparent

This paper aims to investigate the combination of exogenous and dynamic endogenous variables in professional high mobility patterns. It is based on a panel dataset of the Job Mobilities and Family Lives in Europe research project conducted between 2007 and ...

2017

Integrating geo-biodiversity features in the analysis of landscape patterns

Alexandre Buttler, Alexander Ludwig Johannes Peringer, Ioana Stoicescu

Spatial patterns are deeply linked to ecological processes and this relationship lies at the core of landscape ecology. In turn, landscape patterns are influenced by physical, biological and anthropogenic factors. The aim of this study was to explore how s ...

Elsevier Science Bv2017

Multi-task additive models with shared transfer functions based on dictionary learning

Pascal Frossard, Alhussein Fawzi

Additive models form a widely popular class of regression models which represent the relation between covariates and response variables as the sum of low-dimensional transfer functions. Besides flexibility and accuracy, a key benefit of these models is the ...

Institute of Electrical and Electronics Engineers2017

Applications of Approximate Learning and Inference for Probabilistic Models

Young Jun Ko

We develop approximate inference and learning methods for facilitating the use of probabilistic modeling techniques motivated by applications in two different areas. First, we consider the ill-posed inverse problem of recovering an image from an underdeter ...

EPFL2017

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

Michel Bierlaire, Aurélie Glerum, Amanda Blomberg Stathopoulos, Giovanni Longo, 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

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