Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Concept

Gaussian elimination

Publications associées (29)

Approximate Message Passing With Consistent Parameter Estimation and Applications to Sparse Learning

Michaël Unser, Ulugbek Kamilov

We consider the estimation of an independent and identically distributed (i.i.d.) (possibly non-Gaussian) vector x is an element of R-n from measurements y is an element of R-m obtained by a general cascade model consisting of a known linear transform foll ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Compressed Sensing of Memoryless Sources : A Deterministic Hadamard Construction

Saeid Haghighatshoar

Compressed sensing is a new trend in signal processing for efficient sampling and signal acquisition. The idea is that most real-world signals have a sparse representation in an appropriate basis and this can be exploited to capture the sparse signal by ta ...

EPFL2014

Annealing of UV Ar+ and ArF excimer laser fabricated Bragg gratings: SMF-28e fiber

Hans Georg Limberger, Georgios Violakis

Fiber Bragg gratings fabricated in pristine SMF-28e fibers using pulsed ArF-excimer and cw 244-nm Ar+ laser were annealed using tempering rates from 0.0038 to 0.25 K/s. Demarcation energy mapping allowed for the determination of the frequency factors and t ...

Optical Society of America2014

Node-weighted network design and maximum sub-determinants

Carsten Moldenhauer

We consider the Node-weighted Steiner Forest problem on planar graphs. Demaine et al. showed that a generic primal-dual algorithm gives a 6-approximation. We present two different proofs of an approximation factor of~

3

. Then, we draw a connection to Goem ...

EPFL2014

On Sub-determinants and the Diameter of Polyhedra

Friedrich Eisenbrand, Martin Niemeier, Nicolai Hähnle, Marco Di Summa, Nicolas Bonifas

We derive a new upper bound on the diameter of a polyhedron , where . The bound is polynomial in and the largest absolute value of a sub-determinant of , denoted by . More precisely, we show that the diameter of is bounded by . If is bounded, then we show ...

Springer2014

Variational Gaussian Inference for Bilinear Models of Count Data

Young Jun Ko, Mohammad Emtiyaz Khan

Bilinear models of count data with Poisson distribution are popular in applications such as matrix factorization for recommendation systems, modeling of receptive fields of sensory neurons, and modeling of neural-spike trains. Bayesian inference in such mo ...

2014

Learning with tensors: a framework based on convex optimization and spectral regularization

Quoc Tran Dinh

We present a framework based on convex optimization and spectral regularization to perform learning when feature observations are multidimensional arrays (tensors). We give a mathematical characterization of spectral penalties for tensors and analyze a uni ...

Springer2014

Relation of exact Gaussian basis methods to the dephasing representation: Theory and application to time-resolved electronic spectra

Jiri Vanicek, Miroslav Sulc

We recently showed that the dephasing representation (DR) provides an efficient tool for computing ultrafast electronic spectra and that further acceleration is possible with cellularization [M. Šulc and J. Vaníček, Mol. Phys. 110, 945 (2012)]. Here, we fo ...

American Institute of Physics2013

Constrained expectation-maximization algorithm for stochastic inertial error modeling: study of feasibility

Jan Skaloud, Stéphane Guerrier, Yannick Stebler

Stochastic modeling is a challenging task for low-cost sensors whose errors can have complex spectral structures. This makes the tuning process of the INS/GNSS Kalman filter often sensitive and difficult. For example, first-order Gauss–Markov processes are ...

IOP Publishing2011

Publications associées (29)

3

. Then, we draw a connection to Goem ...

EPFL2014

Relation of exact Gaussian basis methods to the dephasing representation: Theory and application to time-resolved electronic spectra

Jiri Vanicek, Miroslav Sulc

American Institute of Physics2013

Constrained expectation-maximization algorithm for stochastic inertial error modeling: study of feasibility

Jan Skaloud, Stéphane Guerrier, Yannick Stebler

IOP Publishing2011