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SeminÃrios de Probabilidade e Sistemas Complexos no ICMC-USP, SÃo Carlos



Prezados colegas,

Gostaria de chamar a atenÃÃo nas palestras que teremos nesta semana (QUINTA 29/05) no contexto dos SeminÃrios de Probabilidade e Sistemas Complexos, organizados em conjunto entre pesquisadores do ICMC-USP e da UFSCar, em SÃo Carlos/SP. SerÃo duas palestras proferidas por pesquisadores que estÃo visitando o ICMC.

SeminÃrio 1: Non-singularity of symmetric random matrices

Palestrante: Rahul Roy (Indian Statistical Institute)
Quando: quinta-feira, 29 de maio, Ãs 16h10
Onde: sala 3-009 (ICMC)

Abstract:
We obtain the almost sure non-singularity of general Wigner ensembles of random matrices when the distribution of the entries are independent but not necessarily identically distributed and may depend on the size of the matrix. These models include adjacency matrices of random graphs and also sparse, generalized, universal and banded random matrices. We find universal rates of convergence and precise estimates for the probability of singularity which depend only on the size of the biggest jump of the distribution functions governing the entries of the matrix. Our proofs are based on a concentration function inequality due to Kesten and allows us to improve the known rates of convergence for the Wigner case when the distribution of the entries do not depend on the size of the matrix. This is joint work with Paulo Manrique and Victor PÃrez-Abreu.

SeminÃrio 2: Optimal stopping for partially observed piecewise-deterministic Markov processes
Palestrante: Benoite de Saporta (Inria Bordeaux Sud Ouest, Equipe CQFD)
Quando: quinta-feira, 29 de maio, Ãs 17h30
Onde: sala 3-009 (ICMC)


Abstract: This talk deals with the optimal stopping problem under partial observation for piecewise-deterministic Markov processes (PDMPs). PDMPs have been introduced by Davis in the literature as a general class of stochastic models. They form a family of Markov processes involving deterministic motion punctuated by random jumps. We first obtain a recursive formulation of the optimal filter process and derive the dynamic programming equation of the partially observed optimal stopping problem. Then, we propose a numerical method, based on the quantization of the discrete-time filter process and the inter-jump times, to approximate the value function and to compute an epsilon-optimal stopping time. We prove the convergence of the algorithms and bound the rates of convergence. This is a joint work with Adrien Brandejsky and FranÃois Dufour.

SÃo todos bem vindos.

Um abraÃo.

Pablo MartÃn RodrÃguez
Professor Doutor (MS-3)
Department of Applied Mathematics and Statistics, ICMC-USP
C.P. 668 - SÃo Carlos, SP, Brazil - CEP 13560-970