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- Path: sparky!uunet!mcsun!uknet!gdt!aber!dbk
- From: dbk@aber.ac.uk (D B Kell)
- Newsgroups: comp.ai.neural-nets
- Subject: Re: Learning what COULD be learned
- Message-ID: <1992Jul21.082035.8898@aber.ac.uk>
- Date: 21 Jul 92 08:20:35 GMT
- References: <1992Jul7.074650.27125@aber.ac.uk> <13uievINN1mp@iraul1.ira.uka.de> <arms.711663417@spedden>
- Organization: University of Wales, Aberystwyth
- Lines: 15
-
- In article <arms.711663417@spedden> arms@cs.UAlberta.CA (Bill Armstrong) writes:
- >The impediment to learning of one output by others that are difficult
- >or impossible is closely related to the "Why not trees?" question I
- >am asking. If you use trees, this harmful interaction can't occur.
- >
- >--
- >***************************************************
- >Prof. William W. Armstrong, Computing Science Dept.
- >University of Alberta; Edmonton, Alberta, Canada T6G 2H1
- >arms@cs.ualberta.ca Tel(403)492 2374 FAX 492 1071
-
- Please elaborate much more explicitly! **HOW** do the trees flag that
- some things are not learnable, others are.
-
- Douglas Kell.
-