| dc.contributor.author | Schmidt, DF | |
| dc.contributor.author | Makalic, E | |
| dc.contributor.editor | Nicholson, A | |
| dc.contributor.editor | Li, X | |
| dc.date.available | 2014-05-21T22:53:54Z | |
| dc.date.issued | 2009-01-01 | |
| dc.identifier | http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000276823500032&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=d4d813f4571fa7d6246bdc0dfeca3a1c | |
| dc.identifier.citation | Schmidt, D. F. & Makalic, E. (2009). MML Invariant Linear Regression. AI 2009: ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 5866, pp.312-315. https://doi.org/10.1007/978-3-642-10439-8_32. | |
| dc.identifier.issn | 0302-9743 | |
| dc.identifier.uri | http://hdl.handle.net/11343/29323 | |
| dc.language | English | |
| dc.publisher | SPRINGER-VERLAG BERLIN | |
| dc.subject | Artificial Intelligence and Image Processing | |
| dc.title | MML Invariant Linear Regression | |
| dc.type | Journal Article | |
| dc.identifier.doi | 10.1007/978-3-642-10439-8_32 | |
| melbourne.peerreview | Peer Reviewed | |
| melbourne.affiliation | The University of Melbourne | |
| melbourne.affiliation.department | Population Health | |
| melbourne.source.title | AI 2009: ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS | |
| melbourne.source.volume | 5866 | |
| melbourne.source.pages | 312-315 | |
| dc.description.pagestart | 312 | |
| melbourne.publicationid | 141548 | |
| melbourne.elementsid | 320727 | |
| melbourne.contributor.author | Schmidt, Daniel | |
| melbourne.contributor.author | Makalic, Enes | |
| dc.identifier.eissn | 1611-3349 | |
| melbourne.accessrights | This item is currently not available from this repository | |
