LEADER 00000nam 2200433 a 4500 001 EBC3338578 003 MiAaPQ 006 m o d | 007 cr cn||||||||| 008 060707s2007 maua sb 001 0 eng 010 |z2006046646 020 |z0262072815 (alk. paper) 020 |z9780262072816 (hbk.) 035 (MiAaPQ)EBC3338578 035 (Au-PeEL)EBL3338578 035 (CaPaEBR)ebr10173636 035 (CaONFJC)MIL209635 035 (OCoLC)123173836 040 MiAaPQ|cMiAaPQ|dMiAaPQ 050 4 QA276.9|b.G78 2007 100 1 Gr?unwald, Peter D. 245 14 The minimum description length principle|h[electronic resource] /|cPeter D. Gr?unwald. 260 Cambridge, Mass. :|bMIT Press,|cc2007. 300 1 online resource (xxxii, 703 p.) :|bill. 490 1 Adaptive computation and machine learning 504 Includes bibliographical references (p. [651]-673) and indexes. 533 Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries. 650 0 Minimum description length (Information theory) 655 7 Electronic books|2local 710 2 ProQuest (Firm) 830 0 Adaptive computation and machine learning. 856 40 |uhttp://sherman.library.nova.edu/auth/index.php?aid=1520& url=https://ebookcentral.proquest.com/lib/novasoutheastern /detail.action?docID=3338578|zAvailable via Ebook Central; click here for access<br /><img class="wb_perm_icon" src=" /screens/wb_cond_11.gif" alt="Local access for all registered users. Remote access only for NSU, Broward, and Alumni."> 935 |z0262072815 (alk. paper) 935 |z9780262072816 (hbk.) 948 jlee1 948 Academic Complete subscription collection
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