### Seminari

### Prossimi Seminari

**Dealing with unreliable computing platforms at extreme scale**

Luc Giraud, INRIA (Inria Bordeaux – Sud-Ouest)

mercoledì 23 gennaio 2019 alle ore 14:00, Aula Consiglio VII Piano – Edificio 14, Dipartimento di Matematica POLITECNICO DI MILANO**Poroelasticity: Discretizations and fast solvers based on geometric multigrid methods**

Francisco José Gaspar Lorenz, Department of Applied Mathematics -Zaragoza University – Spain

giovedì 31 gennaio 2019 alle ore 14:00, Sala Consiglio VII Piano – Edificio 14, Dipartimento di Matematica POLITECNICO DI MILANO**Application of Polyconvexity and multivariable convexity of energy potentials in nonlinear solid mechanics**

Javier Bonet, University of Greenwich

giovedì 14 febbraio 2019 alle ore 14:00, Aula Consiglio VII Piano – Edificio 14, Dipartimento di Matematica POLITECNICO DI MILANO

### Seminari Passati

**Quasistationary Penrose-Fife Model with Neumann Boundary Conditions**

Anastasia Klepatcheva, Dip. di Matematica Politecnico di Milano

giovedì 15 maggio 2003**The classical limit of the relativistic Vlasov-Maxwell system in two space dimensions**

Hayoung Lee Max Planck, Institute for Gravitational Physics

giovedì 15 maggio 2003**Il sistema solare: un orologio perfetto o una Babele ben mascherata? (I parte)**

A. Giorgilli, Univ. Milano Bicocca

mercoledì 14 maggio 2003 alle ore 12:30, aula consiglio VII piano**Blackholes vs. naked singularities formation in gravitational collapse: analytical and numerical results and perspectives.**

Giulio Magli, Dipartimento di matematica F. Brioschi

lunedì 12 maggio 2003 alle ore 14:30, aula seminari MOX- 6° piano dip. matem.ABSTRACTIn 1969 Roger Penrose proposed the so called Cosmic Censorship

conjecture, namely the idea that all gravitating systems

undergoing complete gravitational collapse – such as very massive

stars – should always form blackholes. In other words, the

conjecture states that all singularities eventually forming will

be safely hidden to far-away observers by a event horizon. From

the mathematical point of view the conjecture can be read off as

a characterization of the geodesic motion (governed by o.d.e.) in

a gravitational field assumed to be a solution of the Einstein

field equations (a system of p.d.e.), with the addition of

reasonable physical assumptions. No proof of the conjecture is

available so far, while several examples of physically sound

systems exhibiting naked singularities have been found. In recent

years, the application of techniques coming from non-linear

o.d.e. analysis allowed to construct a new mathematical framework

for censorship experiments which can be used in problems so far

considered unsolvable, such as the gravitational collapse of

barotropic perfect fluids. Parallel, relevant results obtained by

other groups working in the numerical simulation of gravitational

collapse will also be reviewed.

**Estimating Unobserved Probability and the Number of Unobserved Outcomes of an Experiment**

Chelluri C.A. Sastri, Dalhousie University, Halifax (Canada)

lunedì 12 maggio 2003 alle ore 16:00, Dipartimento di Matematica e Applicazioni – Università degli Studi di Milano Bicocca – Via Bicocca degli Arcimboldi, 8 – Aula 371ABSTRACTSuppose that an experiment with an unknown, possibly infinite, number of outcomes is performed and that these outcomes occur according to some random mechanism. Suppose that n independent trials are carried out and that N distinct outcomes have been observed. We attempt to answer the following questions: What is the probability that, on the next trial, an outcome not observed before occurs? (This is called the problem of unobserved probability.) What is the total number of outcomes not observed? This second problem has a long history going back to Turing and is, apart from its mathematical interest, important in many areas such as biology (species sampling), numismatics, and literary scholarship. We’ll give a brief survey of past work and also discuss recent joint work with Alberto Gandolfi in which a Bayes-like estimator for the number of unobserved outcomes is derived. This has the advantage over the existing estimators — due to Chao and Lee and others — in that, modulo the fact that Turing’s ansatz is used (it is used by everyone else as well), it is derived from first principles, without any ad hoc assumptions, and includes previous estimators as special cases. We’ll also briefly discuss an almost complete classification of infinite discrete probability measures, which emerges as a by-product of a solution we have obtained for the problem of unobserved probability.**Presentazione del Corso di Studi in Ingegneria Matematica**

Proff. A.Quarteroni, F.Saleri, S.Salsa, P.Secchi, A.Veneziani

sabato 10 maggio 2003 alle ore 09:30, Aula S05 (replica ore 11:30 e 14:45, stessa aula)**A variational approach to double-porosity problems**

Valeria Chiad•, Piat Dip. di Matematica Politecnico di Torino

mercoledì 7 maggio 2003**3D Computer Vision and Pattern Recognition: Recent Activities at the VIPS Laboratories**

Vittorio Murino, Dip. di Informatica – Univ. degli Studi di Verona

lunedì 5 maggio 2003 alle ore 11:00, Aula Seminari MOX – 6° piano – Dip. MatematicaABSTRACTIn this talk, a general overview of the activities carried out at the

Vision, Image Processing and Sound (VIPS) laboratory (Department of

Computer Science, University of Verona, Italy), and the main research

projects in which it is involved will be described.

The laboratory is involved in a broad spectrum of activities, mainly in

the areas of Computer Vision, Pattern Recognition, and Human-Computer

Interaction.

In particular, the talk will focus on the following research topics:

– 3D Computer Vision: 3D data registration and reconstruction, mosaicing,

view synthesis, augmented reality.

– Pattern Recognition: object detection and classification in remote

sensing images, Hidden Markov models for classification and

videosurveillance applications, face recognition.

Depending on the audience interest and the available time, some issues

can be more detailed.

In particular, the lab is working from long time on methods for the

automatic environment reconstruction from multiple 3D images, and in

exploring Hidden Markov Models (HMMs) for 2D shape classification, and

background detection.