Conference paper

Posterior regularization and attribute assessment of under-determined linear mappings


Authors listStrickert, Marc; Seifert, Michael

Appeared inESANN 2012, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning

Editor listVerleysen, Michel

Publication year2012

Pages67-72

ISBN978-2-87419-047-6

URLhttps://www.esann.org/sites/default/files/proceedings/legacy/es2012-4.pdf

Conference20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning


Abstract

Linear mappings are omnipresent in data processing analysis ranging from regression to distance metric learning. The interpretation of coefficients from under-determined mappings raises an unexpected challenge when the original modeling goal does not impose regularization. Therefore, a general posterior regularization strategy is presented for inducing unique results, and additional sensitivity analysis enables attribute assessment for facilitating model interpretation. An application to infrared spectra reects data smoothness and indicates improved generalization.




Authors/Editors




Citation Styles

Harvard Citation styleStrickert, M. and Seifert, M. (2012) Posterior regularization and attribute assessment of under-determined linear mappings, in Verleysen, M. (ed.) ESANN 2012, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Louvain-la-Neuve: Ciaco. pp. 67-72. https://www.esann.org/sites/default/files/proceedings/legacy/es2012-4.pdf

APA Citation styleStrickert, M., & Seifert, M. (2012). Posterior regularization and attribute assessment of under-determined linear mappings. In Verleysen, M. (Ed.), ESANN 2012, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. (pp. 67-72). Ciaco. https://www.esann.org/sites/default/files/proceedings/legacy/es2012-4.pdf


Last updated on 2025-06-06 at 15:25