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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Stochastic approximation in Hilbert spaces.

Apprentissage supervisé, Approximation stochastique, Convex optimization, Espaces de Hilbert à noyaux reproduisants, Estimation non-paramétrique, Nonparametric estimation, Optimisation convexe, Reproducing kernel Hilbert spaces, Stochastic approximation, Supervised learning

On asymptotics of the discrete convex LSE of a pmf.

Convex, Least squares, Nonparametric estimation, Pmf, Shape-constraints

Efficient volatility estimation in a two‐factor model.

Discrete observations, Electricity market modelling, Financial statistics, HJM models, Nonparametric estimation, Semipara-metric efficient bounds, Time-to-maturity factor

Efficient volatility estimation in a two-factor model.

Discrete observations, Electricity market modelling, Financial statistics, HJM models, Nonparametric estimation, Semipara-metric efficient bounds, Time-to-maturity factor

Statistical inference across scales.

Discretely observed random process, Estimation nonparamétrique, Information statistique, Nonparametric estimation, Processus de renouvellement, Processus observé à temps discret, Renewal reward process, Statistical information

Nonparametric estimation of the division rate of an age dependent branching process.

Bellman-Harris processes, Bias selection, Cell division, Growth-fragmentation, Min-imax rates of convergence, Nonparametric estimation

Nonparametric estimation of the division rate of an age dependent branching process.

Bellman-Harris processes, Bias selection, Cell division, Growth-fragmentation, Min-imax rates of convergence, Nonparametric estimation

Statistical estimation of a growth-fragmentation model observed on a genealogical tree.

35B40, Cell division equation, Growth-fragmentation, Markov chain on a tree Mathematical Subject Classification 35A05, Nonparametric estimation

Nonparametric estimation of the fragmentation kernel based on a partial differential equation stationary distribution approximation.

35B40, 45K05, 60J80, 92D25, Cell division, Deconvolution, Growth-fragmentation, Kernel rule, MSC2010 62G07, Nonparametric estimation

Nonparametric estimation of conditional densities: high dimensionality, parsimony and gluttonous algorithms.

Algorithmes gloutons, Conditional density, Densité conditionnelle, Estimateurs à noyau, Estimation non paramétrique, Grande dimension, Greedy algorithms, High dimension, Kernel density estimators, Nonparametric estimation, Parcimonie, Sparsity

Nonparametric estimation of the fragmentation kernel based on a PDE stationary distribution approximation.

Cell division, Deconvolution, Growth-fragmentation, Kernel rule, Nonparametric estimation

High dimensional density estimation and curve classification.

Apprentissage statistique, Classification de courbe, Coefficient de pulvérisation, Combinatorial method, Curve classification, Dynamical system, Estimateur à noyau variable, Estimation non paramétrique, Histogramme modifié, Modified histogram, Méthode combinatoire, Nonparametric estimation, Ondelettes, Shatter coefficient, Statistical learning, Système dynamique, Variable kernel density estimate, Wavelets