Toulouse 1 Capitole Publications
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Covid-19 impact on Bike-sharing systems: An analysis for Toulouse, Lyon, and Montreal
No full textBased on Bike-sharing system (BSS) data for Toulouse, Lyon, and Montreal, we study the Covid19 impact on relevant variables of BSS use. Our results show significant changes related to longer travel distance, which would be explained by those users who use the BSS at peak hour. Also, after Covid-19 outbreak there is evidence about higher willingness to use the BSS in adverse weather conditions (such as rain and wind), lower substitution with the public transport system in Lyon, and a recovery and even a slight increase of BSS trips for Toulouse and Lyon respectively. In our opinion, these results most likely represent permanent changes in user’ habits, being an excellent opportunity to make specific investments in this system and thus strongly
promote the bicycle use and its permanence
Nonsmooth Implicit Differentiation for Machine Learning and Optimization
No full textIn view of training increasingly complex learning architectures, we establish a nonsmooth implicit function theorem with an operational calculus. Our result applies to most practical problems (i.e., definable problems) provided that a nonsmooth form of the classical invertibility condition is fulfilled. This approach allows for formal subdifferentiation: for instance, replacing derivatives by Clarke Jacobians in the usual differentiation formulas is fully justified for a wide class of nonsmooth problems. Moreover this calculus is entirely compatible with algorithmic differentiation (e.g., backpropagation). We provide several applications such as training deep equilibrium networks, training neural nets with conic optimization layers, or hyperparameter-tuning for nonsmooth Lasso-type models. To show the sharpness of our assumptions, we present numerical experiments showcasing the extremely pathological gradient dynamics one can encounter when applying implicit algorithmic differentiation without any hypothesis
How landownership equality created a low wage society: pre-industrial Japan, 1600-1870
No full textDespite its sophistication, Early Modern Japan, 1600-1868, had among the lowest real wage levels ever recorded, half of those in pre-industrial England. This paper resolves this puzzle by considering the more equal landownership distribution in Japan relative to Europe. Due to institutional differences in land transmission, most of the rural population were landless in England but only 16% in Japan circa 1800. Using a Malthusian model, I show landownership equality in Japan paradoxically generated lower wages and GDP per capita. This is due to the concavity in the positive income-fertility curve resulting in greater equality generating greater population pressures. I provide evidence of the mechanism at the cross-country level and at the individual level using Japanese village censuses. If, as many historians believe, high wages in western Europe explain the onset of the Industrial Revolution, then Japan’s failure to industrialize first could have been shaped by its unusual pre-industrial equality
Collectivités outre-mer et environnement
No full textUne étude du droit de l'environnement (biodiversité, pollutions, risques) dans les outremer françai
Partage de la pension de réversion entre conjoints survivants en présence d'un mariage putatif (Cass. 2° civ., 21 oct. 2021)
No full text
Les pratiques de Facebook en matière de lecture, d'écriture et de dépôt de cookies épinglées par la CNIL
No full textA propos du rôle de l’élu local : les tourments d’un élu en charge de politiques culturelles
No full textQuel est le rôle d’un élu local?
Par un retour d’expérience, nous voudrions témoigner des tourments vécus par un élu local en charge plus particulièrement de politiques culturelles. Ceux-ci sont liés au mode de fonctionnement d’une collectivité territoriale (I), aux rapports élus-administration en son sein (II) et à l’identification des missions de service public culturel à mener (III)
On the usage of joint diagonalization in multivariate statistics
No full textScatter matrices generalize the covariance matrix and are useful in many multivariate data analysis methods, including well-known principal component analysis (PCA), which is based on the diagonalization of the covariance matrix. The simultaneous diagonalization of two or more scatter matrices goes beyond PCA and is used more and more often. In this paper, we offer an overview of many methods that are based on a joint diagonalization. These methods range from the unsupervised context with invariant coordinate selection and blind source separation, which includes independent component analysis, to the supervised context with discriminant analysis and sliced inverse regression. They also encompass methods that handle dependent data such as time series or spatial data