Patrimony

The Louis Bachelier Group's patrimony has been defined as all the publications produced by academic researchers thanks to Group funding (ILB, FdR, IEF, Labex) or via the use of EquipEx data (BEDOFIH, EUROFIDAI).


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Linear regression and learning: contributions to regularization and aggregation methods.

Aggregation, Agrégation, Apprentissage, Empirical processes, Learning, Linear regression, Online convex optimization, Optimisation convexe séquentielle, Processus empiriques, Regularization, Régression linéaire, Régularisation

On unsupervised learning in high dimension.

Aggregation, Agr?gation, Clustering, Density estimation, Estimation de densit?, Gaussian mixtures, Grande dimension, High dimension, M?lange de gaussiennes

Dependence modeling for order statistics and non-parametric estimation.

Aggregation, Agrégation, Copula, Copule, Diagonal, Diagonale, Entropie, Entropy, Estimation non-Paramétrique, Nonparametric estimation, Order statistics, Statistics d'ordre

One-Year Volatility of Reserve Risk in a Multivariate Framework.

Aggregation, Claims development result, Correlation, Dependency, Estimation error, Lines of business, Multivariate reserving, One-year multivariate reserve risk, Prediction error, Process error, Run-off portfolio, Solvency II

Aggregation using input-output trade-off.

Aggregation, Classification, Consistency, Nonlinearity, Regression estimation

Aggregation using input–output trade-off.

Aggregation, Classification, Consistency, Nonlinearity, Regression estimation

A clusterwise supervised learning procedure based on aggregation of distances.

62P30, 68T05, 68U99, 68U99 1, Aggregation, Bregman divergences, Classification, Clustering, Kernel 2010 Mathematics Subject Classification 62J99, Kernel 22 2010 Mathematics Subject Classification 62J99, Re- 21 gression, Re- gression