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Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization

Publications associées (62)

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A path integral formalism of DNA looping probability

Ludovica Cotta-Ramusino

In this thesis we describe a path integral formalism to evaluate approximations to the probability density function for the location and orientation of one end of a continuum polymer chain at thermodynamic equilibrium with a heat bath. We concentrate on th ...

EPFL2008

Cross-Validation Optimization for Large Scale Structured Classification Kernel Methods

Matthias Seeger

We propose a highly efficient framework for penalized likelihood kernel methods applied to multi-class models with a large, structured set of classes. As opposed to many previous approaches which try to decompose the fitting problem into many smaller ones, ...

Massachusetts Institute of Technology Press2008

Block variants of Hammarling's method for solving Lyapunov equations

Daniel Kressner

This article is concerned with the efficient numerical solution of the Lyapunov equation A(T) X + XA = -C with a stable matrix A and a symmetric positive semidefinite matrix C of possibly small rank. We discuss the efficient implementation of Hammarling's ...

Association for Computing Machinery2008

Multiparametric Linear Complementarity Problems

Colin Neil Jones

The linear complementarity problem (LCP) is a general problem that unifies linear and quadratic programs and bimatrix games. In this paper, we present an efficient algorithm for the solution to multiparametric linear complementarity problems (pLCPs) that a ...

IEEE2006

Trust-region methods based on radial basis functions with application to biomedical imaging

Rodrigue Oeuvray

We have developed a new derivative-free algorithm based on Radial Basis Functions (RBFs). Derivative-free optimization is an active field of research and several algorithms have been proposed recently. Problems of this nature in the industrial setting are ...

EPFL2005

A polynomial case of inconstrained zero-one queadratic optimization

Thomas Liebling, Kim Alexandre Allemand

Unconstrained zero-one quadratic maximization problems can be solved in polynomial time when the symmetric matrix describing the objective function is positive semidefinite of fixed rank with known spectral decomposition. ...

2001

The Degenerate Bounded Errors-in-Variables Model

Ali H. Sayed

We consider the following problem:

\min_{x \in {\cal R}^n} \min_{\|E\| \le \eta} \|(A+E)x-b\|

, where A is an

m \times n

real matrix and b is an n-dimensional real column vector when it has multiple global minima. This problem is an errors-in-variables ...

2001

Displacement Structure and H ∞ Problems

Ali H. Sayed

The solution of H∞ problems requires the determination of contractive operators that map certain input signals to certain output signals. Such operators, and tests for their contractiveness, arise naturally in a scattering formulation of the generalized Sc ...

Springer2000

Stabilizing the Generalized Schur Algorithm

Ali H. Sayed

This paper provides a detailed analysis that shows how to stabilize the generalized Schur algorithm, which is a fast procedure for the Cholesky factorization of positive-definite structured matrices R that satisfy displacement equations of the form $R - FR ...

Society for Industrial and Applied Mathematics1996

Error-energy bounds for adaptive gradient algorithms

Ali H. Sayed

The paper establishes robustness, optimality, and convergence properties of the widely used class of instantaneous-gradient adaptive algorithms. The analysis is carried out in a purely deterministic framework and assumes no a priori statistical information ...

IEEE1996

The Degenerate Bounded Errors-in-Variables Model

Ali H. Sayed

We consider the following problem:

\min_{x \in {\cal R}^n} \min_{\|E\| \le \eta} \|(A+E)x-b\|

, where A is an

m \times n

real matrix and b is an n-dimensional real column vector when it has multiple global minima. This problem is an errors-in-variables ...

2001