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Publications associées (150)

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Non-convex, non-local functionals converging to the total variation

Hoài-Minh Nguyên

We present new results concerning the approximation of the total variation, integral(Omega)vertical bar del u vertical bar, of a function u by non-local, non-convex functionals of the form Lambda delta(u) = integral(Omega)integral(Omega)delta phi(vertical ...

Elsevier2017

Representing groups against all odds

Maxime Gheysens

We investigate how probability tools can be useful to study representations of non-amenable groups. A suitable notion of "probabilistic subgroup" is proposed for locally compact groups, and is valuable to induction of representations. Nonamenable groups ad ...

EPFL2017

Spline Shape Processing

Daniel Andreas Schmitter

In this thesis, we present a novel generic and unifying framework for data-adaptive shape modeling. Our work is motivated by the raising need for powerful geometric modeling kernels that are required for shape characterization in biomedical imaging. The on ...

EPFL2017

Shape Projectors for Landmark-Based Spline Curves

Michaël Unser, Daniel Andreas Schmitter

We present a generic method to construct orthogonal projectors for two-dimensional landmark-based parametric spline curves. We construct vector spaces that define a geometric transformation (e.g., affine, similarity, and scaling) that is applied to a refer ...

2017

Optical Tomography Based On A Nonlinear Model That Handles Multiple Scattering

Michaël Unser, Demetri Psaltis, Ulugbek Kamilov, Alexandre Goy, Joowon Lim

Learning Tomography (LT) is a nonlinear optimization algorithm for computationally imaging three-dimensional (3D) distribution of the refractive index in semi-transparent samples. Since the energy function in LT is generally non-convex, the solution it obt ...

Ieee2017

Multidimensional Persistence and Noise

Martina Scolamiero

In this paper, we study multidimensional persistence modules (Carlsson and Zomorodian in Discrete Comput Geom 42(1):71-93, 2009; Lesnick in Found Comput Math 15(3):613-650, 2015) via what we call tame functors and noise systems. A noise system leads to a p ...

Springer2017

Robust optimal control with adjustable uncertainty sets

Maryam Kamgarpour, John Lygeros, Xiaojing Zhang

In this paper, we develop a unified framework for studying constrained robust optimal control problems with adjustable uncertainty sets. In contrast to standard constrained robust optimal control problems with known uncertainty sets, we treat the uncertain ...

2017

On the well-posedness of the Holm-Staley b-family of equations

Hasan Inci

In this paper we consider the Holm-Staley b-family of equations in the Sobolev spaces H-s (R) for s > 3/2. Using a geometric approach we show that, for any value of the parameter b, the corresponding solution map, u(0) bar right arrow u(T), is nowhere loca ...

Taylor & Francis Ltd2016

Space lower bounds for low-stretch greedy embeddings

Christos Kalaitzis

Greedy (geometric) routing is an important paradigm for routing in communication networks. It uses an embedding of the nodes of a network into points of a space (e.g., R-d) equipped with a distance function (e.g., the Euclidean distance l(2)) and uses as a ...

Elsevier Science Bv2016

Separation with restricted families of sets

János Pach, Gábor Tardos, Márton Naszódi, Zsolt Langi

Given a finite n-element set X, a family of subsets F subset of 2(X) is said to separate X if any two elements of X are separated by at least one member of F. It is shown that if vertical bar F vertical bar > 2(n-1), then one can select vertical bar log n ...

Academic Press Inc Elsevier Science2016