Solution of the pre-image problem is key to efficient non-linear de-noising using kernel
Principal Component Analysis. Pre-image estimation is inherently ill-posed for typical
kernels used in applications and consequently the most widely used estimation schemes
lack stability. For de-noising applications we propose input space distance regularization as
a stabilizer for pre-image estimation. We perform extensive experiments on the USPS digit
modeling problem to evaluate the stability of three widely used pre-image estimators. We …

Solution of the pre-image problem is key to efficient nonlinear de-noising using kernel
Principal Component Analysis. Pre-image estimation is inherently ill-posed for typical
kernels used in applications and consequently the most widely used estimation schemes
lack stability. For de-noising applications we propose input space distance regularization as
a stabilizer for pre-image estimation. We perform extensive experiments on the USPS digit
modeling problem to evaluate the stability of three widely used pre-image estimators. We …