The more recent work by G. E. Hinton brought here by Ed Porter is very interesting mathematically (if you go into the details of trying to argument why it works -- probabilistic modeling "a la" graphical models).
On Thu, Oct 9, 2008 at 12:32 AM, Ben Goertzel <[EMAIL PROTECTED]> wrote: > > For neural nets, Daniel Amit had a good book in the 80's reviewing the > dynamics > of attractor neural nets ... > On Wed, Oct 8, 2008 at 6:25 PM, Vladimir Nesov <[EMAIL PROTECTED]> wrote: >> >> Read an introductory text on machine learning to get up to speed -- >> it's the math of AI, and there's lots of it. Statistics, information >> theory. It's an important perspective from which to look at less well >> understood hacks, to feel the underlying structure. ------------------------------------------- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
