J. Larsen, L. K. Hansen, C. Svarer, M. Ohlsson
Abstract- In this paper we derive novel algorithms for estimation of regularization parameters and for optimization of neural net architectures based on a validation set. Regularization parameters...
C. Goutte, F. A. Nielsen, C. Svarer, E. Rostrup, L. K. Hansen, Rigshospitalet Denmark
Feature-space clustering The high temporal resolution of fMRI has inspired a host of single-voxel analysis methods. They typically compute some summary statistics characterising the temporal response...
P. Toft, L. K. Hansen, F. A. Nielsen, S. C. Strother, N. Lange, N. Mrch, ...
5, B. Rosen 5, E. Rostrup 6, P. Born
Adaptive regularization (1994)
L. K. Hansen, C. E. Rasmussen, C. Svarer, J. Larsen
Abstract. Regularization, e.g., in the form of weight decay, is important for training and optimization of neural network architectures. In this work we provide a tool based on asymptotic sampling...
Designer networks for time series processing (1993)
C. Svarer, L. K. Hansen, J. Larsen, C. E. Rasmussen
The conventional Tapped-Delay Neural Net [14] may be analyzed using statistical methods and the results of such analysis can be applied to model optimization. In this presentation we review and...