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Publications associées (8)

Deep Learning Meets Sparse Regularization

Rahul Parhi

Deep learning (DL) has been wildly successful in practice, and most of the state-of-the-art machine learning methods are based on neural networks (NNs). Lacking, however, is a rigorous mathematical theory that adequately explains the amazing performance of ...

2023

Switchover phenomenon induced by epidemic seeding on geometric networks

Gergely Odor

It is a fundamental question in disease modeling how the initial seeding of an epidemic, spreading over a network, determines its final outcome. One important goal has been to find the seed configuration, which infects the most individuals. Although the id ...

2021

Mutual Information for the Stochastic Block Model by the Adaptive Interpolation Method

Nicolas Macris, Jean François Emmanuel Barbier, Chun Lam Chan

We rigorously derive a single-letter variational expression for the mutual information of the asymmetric two-groups stochastic block model in the dense graph regime. Existing proofs in the literature are indirect, as they involve mapping the model to a ran ...

IEEE2019

A Low-Power Correlator for Wakeup Receivers with Algorithm Pruning through Early Termination

Andreas Peter Burg, Adam Shmuel Teman, Jeremy Hugues-Felix Constantin, Reza Ghanaatian Jahromi

A low-complexity, low-power digital correlator for wakeup receivers is presented. With the proposed algorithm, unnecessary computational cycles are dynamically pruned from the correlation using an early threshold check. For the algorithm, we provide a rigo ...

Ieee2016

Superlensing using complementary media

Hoài-Minh Nguyên

This paper studies magnifying superlens using complementary media. Superlensing using complementary media was suggested by Veselago in [16] and innovated by Nicorovici et al. in [9] and Pendry in [10]. The study of this problem is difficult due to two fact ...

EMS Press2015

Bifurcation Analysis at a Singular Soliton State in Fiber Couplers

Boris Buffoni

The system {-u '' + u = u(3) + lambda v, u(x)= u(-x) is an element of R, x is an element of R, -v '' + v = v(3) + lambda u, v(x) = v(-x) is an element of R, x is an element of R, describes pulses in nonlinear fiber couplers. It has the family (U1+lambda, - ...

Advanced Nonlinear Studies, Inc2012

The Solution of Nonlinear Function of Ion Mobility Based on FAIMS Spectrum Peak Position

Jürgen Brugger

FAIMS's ion separation mechanism is based on analyte's characteristic nonlinear relationship between its ion mobility and applied electric field strength. Present characterization methods for this nonlinear relationship are based on precarious assumptions ...

Office Spectroscopy & Spectral Analysis2012

Asymptotics and analytic modes for the wave equation in similarity coordinates

Roland Donninger

We consider the radial wave equation in similarity coordinates within the semigroup formalism. It is known that the generator of the semigroup exhibits a continuum of eigenvalues and embedded in this continuum there exists a discrete set of eigenvalues wit ...

Springer Verlag2009