6533b855fe1ef96bd12b0453
RESEARCH PRODUCT
Recursion at the crossroads of sequence modeling, random trees, stochastic algorithms and martingales
Peggy Cénacsubject
modèles auto-régressifs[MATH.MATH-PR] Mathematics [math]/Probability [math.PR]estimation and prediction errorstochastic gradient algorithmschaîne de Markov à mémoire variable[STAT.TH] Statistics [stat]/Statistics Theory [stat.TH]Digital search treesvariable length Markov chainstrong laws for discrete martingalessuffix trietemps d'occurrences de motifsoptimisation stochastique.dynamical systemtrie des suffixesstochastic optimization.erreur d'estimation et de prédictionArbres digitaux de rechercheauto-regressive modelssystème dynamiquelois fortes de martingales discrètesalgorithmes de gradient stochastiques[MATH.MATH-ST] Mathematics [math]/Statistics [math.ST]occurrences timedescription
This monograph synthesizes several studies spanning from dynamical systems in the statistical analysis of sequences, to analysis of algorithms in random trees and discrete stochastic processes. These works find applications in various fields ranging from biological sequences to linear regression models, branching processes, through functional statistics and estimates of risk indicators for insurances. All the established results use, in one way or another, the recursive property of the structure under study, by highlighting invariants such as martingales, which are at the heart of this monograph, as tools as well as objects of study.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2013-01-01 |