Publications associées à On 1-norm stochastic optimal control with bounded control inputs

MATHICSE Technical Report : Low-rank updates and divide-andconquer methods for quadratic matrix equations

In this work, we consider two types of large-scale quadratic matrix equations: Continuous-time algebraic Riccati equations, which play a central role in optimal and robust control, and unilateral quadratic matrix equations, which arise from stochastic proc ...

MATHICSE2019

Convergence of the Exponentiated Gradient Method with Armijo Line Search

Volkan Cevher, Yen-Huan Li

Consider the problem of minimizing a convex differentiable function on the probability simplex, spectrahedron, or set of quantum density matrices. We prove that the expo-nentiated gradient method with Armijo line search always converges to the optimum, if ...

2018

MATHICSE Technical Report : Quasi-Toeplitz matrix arithmetic : a Matlab toolbox

Stefano Massei

A Quasi Toeplitz (QT) matrix is a semi-infinite matrix of the kind

A = T(a) + E

where

T(a) = (aj-i)_{i,j\in \mathbb{Z}_{+}}

,

E = (e_{i,j})_{i,j\in\mathbb{Z}_{+}}

is compact and the norms

\| a\|_{\mathcal{W}} =\sum_{i\in\mathbb{Z}} |a|_j

and $|E|_{ ...

MATHICSE2018

What do gravitons say about (unimodular) gravity?

Mario Herrero Valea

We revisit the problem of constraining the weak field limit of the gravitational lagrangian from S-matrix properties. From unitarity and Lorentz invariance of the S-matrix of massless gravitons, we derive on-shell gauge invariance to consist on the transve ...

SPRINGER2018

MATHICSE Technical Report : Low-rank updates and a divideand- conquer method for linear matrix equations

Daniel Kressner, Stefano Massei

Linear matrix equations, such as the Sylvester and Lyapunov equations, play an important role in various applications, including the stability analysis and dimensionality reduction of linear dynamical control systems and the solution of partial differentia ...

MATHICSE2017

Representer Theorems for Sparsity-Promoting $ ℓ _{ 1 } $ Regularization

Michaël Unser, Julien René Pierre Fageot, Harshit Gupta

We present a theoretical analysis and comparison of the effect of

ℓ _{ 1 }

versus

ℓ _{ 2 }

regularization for the resolution of ill-posed linear inverse and/or compressed sensing problems. Our formulation covers the most general setting where the s ...

IEEE2016

Parallel algorithms for tensor completion in the CP format

Daniel Kressner, André Uschmajew

Low-rank tensor completion addresses the task of filling in missing entries in multidimensional data. It has proven its versatility in numerous applications, including context aware recommender systems and multivariate function learning. To handle large-sc ...

Elsevier Science Bv2016

ALS Scheme using Extent-based Constraints for the Analysis of Chemical Reaction Systems

Dominique Bonvin, Julien Léo Billeter, Michael Amrhein

Multivariate curve resolution via alternating least squares (ALS) is used to resolve the concentration profiles C and the pure component spectra E of S species from the multivariate absorbance data A, assuming the bilinear model ...

2016

Evaluating functions of positive-definite matrices using colored-noise thermostats

Michele Ceriotti, Michele Parrinello

Many applications in computational science require computing the elements of a function of a large matrix. A commonly used approach is based on the the evaluation of the eigenvalue decomposition, a task that, in general, involves a computing time that scal ...

Amer Physical Soc2014

Analytical shape derivatives of the MFIE system matrix discretized with RWG functions

Juan Ramon Mosig

An analytical formula for the shape derivative of the magnetic field integral equation (MFIE) method of moments (MoM) system matrix (or impedance matrix) is derived and validated against finite difference formulas. The motivation for computing the shape de ...

Institute of Electrical and Electronics Engineers2013

On 1-norm stochastic optimal control with bounded control inputs

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MATHICSE Technical Report : Low-rank updates and divide-andconquer methods for quadratic matrix equations

Convergence of the Exponentiated Gradient Method with Armijo Line Search

MATHICSE Technical Report : Quasi-Toeplitz matrix arithmetic : a Matlab toolbox

What do gravitons say about (unimodular) gravity?

MATHICSE Technical Report : Low-rank updates and a divideand- conquer method for linear matrix equations

Representer Theorems for Sparsity-Promoting $ ℓ _{ 1 } $ Regularization

Parallel algorithms for tensor completion in the CP format

ALS Scheme using Extent-based Constraints for the Analysis of Chemical Reaction Systems

Evaluating functions of positive-definite matrices using colored-noise thermostats

Analytical shape derivatives of the MFIE system matrix discretized with RWG functions

MATHICSE Technical Report : Low-rank updates and a divideand- conquer method for linear matrix equations

Evaluating functions of positive-definite matrices using colored-noise thermostats

MATHICSE Technical Report : Low-rank updates and divide-andconquer methods for quadratic matrix equations

Convergence of the Exponentiated Gradient Method with Armijo Line Search

MATHICSE Technical Report : Quasi-Toeplitz matrix arithmetic : a Matlab toolbox

What do gravitons say about (unimodular) gravity?

Representer Theorems for Sparsity-Promoting $ ℓ _{ 1 } $ Regularization

ALS Scheme using Extent-based Constraints for the Analysis of Chemical Reaction Systems

Parallel algorithms for tensor completion in the CP format

Analytical shape derivatives of the MFIE system matrix discretized with RWG functions