Publications related to Rigorous optimization recipes for sparse and low rank inverse problems with applications in data sciences

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Reduction strategies for shape dependent inverse problems in haemodynamics

Gianluigi Rozza, Andrea Manzoni, Toni Mikael Lassila

This work deals with the development and application of reduction strategies for real-time and many query problems arising in fluid dynamics, such as shape optimization, shape registration (reconstruction), and shape parametrization. The proposed strategy ...

Springer2012

Optimizing over the Growing Spectrahedron

Martin Jaggi

We devise a framework for computing an approximate solution path for an important class of parameterized semidefinite problems that is guaranteed to be ε-close to the exact solution path. The problem of computing the entire regularization path for matrix f ...

Springer Berlin Heidelberg2012

Certified Reduced Basis Approximation for Parametrized Partial Differential Equations and Applications

Alfio Quarteroni, Gianluigi Rozza, Andrea Manzoni

Reduction strategies, such as model order reduction (MOR) or reduced basis (RB) methods, in scientic computing may become crucial in applications of increasing complexity. In this paper we review the reduced basis method (built upon a high-delity "truth" f ...

2011

Learning Low-Dimensional Signal Models

Volkan Cevher

Sampling, coding, and streaming even the most essential data, e.g., in medical imaging and weather-monitoring applications, produce a data deluge that severely stresses the avail able analog-to-digital converter, communication bandwidth, and digital-storag ...

Institute of Electrical and Electronics Engineers2011

Moving horizon partition-based state estimation of large-scale systems

Giancarlo Ferrari Trecate, Marcello Farina

This paper presents three novel Moving Horizon Estimation (MHE) methods for discrete-time partitioned linear systems, i.e. systems decomposed into coupled subsystems with non-overlapping states. The MHE approach is used due to its capability of exploiting ...

2010

State estimation for large-scale partitioned systems: a moving horizon approach

Giancarlo Ferrari Trecate, Marcello Farina

2010

An Optimal Algorithm for Reconstructing Images from Binary Measurements

Martin Vetterli, Luciano Sbaiz, Yue Lu, Feng Yang

We have studied a camera with a very large number of binary pixels referred to as the gigavision camera or the gigapixel digital film camera. Potential advantages of this new camera design include improved dynamic range, thanks to its logarithmic sensor re ...

2010

Graph-based classification of multiple observation sets

Pascal Frossard, Effrosyni Kokiopoulou

We consider the problem of classification of multiple observations of the same object, possibly under different transformations. We view this problem as a special case of semi-supervised learning where all unlabelled examples belong to the same unknown cla ...

Elsevier2010

Rigorous optimization recipes for sparse and low rank inverse problems with applications in data sciences

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Reduction strategies for shape dependent inverse problems in haemodynamics

Optimizing over the Growing Spectrahedron

Music Recommendation to Groups

Certified Reduced Basis Approximation for Parametrized Partial Differential Equations and Applications

Learning Low-Dimensional Signal Models

Moving horizon partition-based state estimation of large-scale systems

State estimation for large-scale partitioned systems: a moving horizon approach

An Optimal Algorithm for Reconstructing Images from Binary Measurements

Graph-based classification of multiple observation sets

Fast hard thresholding with Nesterov's gradient method

Music Recommendation to Groups

Optimizing over the Growing Spectrahedron

Learning Low-Dimensional Signal Models

Certified Reduced Basis Approximation for Parametrized Partial Differential Equations and Applications

State estimation for large-scale partitioned systems: a moving horizon approach

Moving horizon partition-based state estimation of large-scale systems

An Optimal Algorithm for Reconstructing Images from Binary Measurements

Reduction strategies for shape dependent inverse problems in haemodynamics

Graph-based classification of multiple observation sets

Fast hard thresholding with Nesterov's gradient method