Seminar Details
2020-02-04 (14:00) : Three 15-minute talks
At Euler building (room A.002)
Organized by Mathematical Engineering
Section 1: Local dynamics identification via a graph-theoretical approach
Speaker :
Legat, Antoine
Abstract :
In this talk we propose a novel approach to network identification: the recovery of the local dynamics from the global input-output behavior and the network structure. First, we express identifiability conditions on the rank of transfer matrices, which can be computed by routing vertex disjoint paths in the network. We then address the unstudied case of partial measurement and excitation, and derive a linearization which yields promising conditions for the identifiability of the whole network, backed up by our implementation.
Section 2: Mathematical modeling of malaria transmission taking into account the influence of current prevention and treatment
Speaker :
Ousmane Diao
Abstract :
Malaria is a parasitic infection transmitted by a mosquito (female Anophele) which is very deadly for humans. Many strategies are provided from the Senegal s National Malaria Control Program of to reduce morbidity and mortality. We have insecticide-treated bed-nets (ITNs), Vaccines, L'Artemisinin-based combination therapy (ACT) and indoor residual spraying (IRS) etc For it, mathematical modelling may play an important role in operational and optimizing this strategies on control. So we want to develop compartments mathematical model of malaria transmission to show the effects of prevention and treatment.
Section 3: Lower bounds for the nonnegative rank
Speaker :
Dewez, Julien
Abstract :
Nonnegative matrix factorization (NMF) consists in finding two nonnegative matrices whose product is equal to/approximates a nonnegative data matrix. It has many interesting applications in data analysis when the observed data is nonnegative by nature, e.g., in text mining, in hyperspectral unmixing, and many more. Computing the minimum dimension of such a factorization, called the nonnegative rank, is NP-hard in general. However, it also has interesting applications, e.g., in combinatorial optimization, in statistics, etc.
In this talk, we introduce new lower bounds on the nonnegative rank based on properties of some geometric representations of the matrix.