This paper addresses the derivation of likelihood functions and confidence bounds for problems involving overdetermined linear systems with noise in all measurements, often referr...
In a recent paper Sima, Van Huffel and Golub [Regularized total least squares based on quadratic eigenvalue problem solvers. BIT Numerical Mathematics 44, 793 - 812 (2004)] sugges...
This paper outlines the ubiquitous presence of generalized orientation (or subspace) estimationproblems in image analysis. We show the potential sources of bias in naive approache...
An important strength of learning classifier systems (LCSs) lies in the combination of genetic optimization techniques with gradient-based approximation techniques. The chosen app...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
Since the seminal work of Stein in the 1950s, there has been continuing research devoted to improving the total meansquared error (MSE) of the least-squares (LS) estimator in the l...