144 citations
- Centre for Research in Engineering Surface TechnologyIE11 papers
- Laboratoire de Probabilités et Modèles AléatoiresFR5 papers
- Centre de Recherche en Mathématiques de la DécisionFR4 papers
- Center for Responsible TravelUS3 papers
- Centre National de la Recherche ScientifiqueFR2 papers
- ENSAE ParisFR2 papers
- Institut Montpelliérain Alexander GrothendieckFR2 papers
- Japan Synchrotron Radiation Research InstituteJP2 papers
- National Institute of Advanced Industrial Science and TechnologyJP2 papers
- Psychiatric Medicine AssociatesUS2 papers
- Science and Technology Corporation (United States)US2 papers
- SPring-8JP2 papers
19 papers
Stability of Feynman-Kac formulae with path-dependent potentials
Nicolas Chopin, Pierre Del Moral, Sylvain Rubenthaler
Several particle algorithms admit a Feynman-Kac representation such that the potential function may be expressed as a recursive function which depends on the complete state traject…
Bayesian Core: The Complete Solution Manual
Christian P. Robert, Jean-Michel Marin
This solution manual contains the unabridged and original solutions to all the exercises proposed in Bayesian Core, along with R programs when necessary.
Importance sampling methods for Bayesian discrimination between embedded models
Jean-Michel Marin, Christian P. Robert
This paper surveys some well-established approaches on the approximation of Bayes factors used in Bayesian model choice, mostly as covered in Chen et al. (2000). Our focus here is…
Double Kernel estimation of sensitivities
Romuald Elie
This paper adresses the general issue of estimating the sensitivity of the expectation of a random variable with respect to a parameter characterizing its evolution. In finance for…
Transductive versions of the LASSO and the Dantzig Selector
Pierre Alquier, Mohamed Hebiri
We consider the linear regression problem, where the number of covariates is possibly larger than the number of observations , under sparsit…
Sparse classification boundaries
Yuri I. Ingster, Christophe Pouet, Alexandre B. Tsybakov
Given a training sample of size from a -dimensional population, we wish to allocate a new observation to this population or to the noise. We suppose that the dif…