Paper
Ganesh Mani
ganesh at cs.wisc.edu
Sun Aug 5 17:59:23 EDT 1990
The following paper is available for ftp from the repository at Ohio State.
Please backpropagate comments (and errors!) to ganesh at cs.wisc.edu.
-Ganesh Mani
_________________________________________________________________________
Learning by Gradient Descent in Function Space
Ganesh Mani
Computer Sciences Dept.
Unviersity of Wisconsin---Madison
ganesh at cs.wisc.edu
Abstract
Traditional connectionist networks have homogeneous nodes
wherein each node executes the same function. Networks where each node
executes a different function can be used to achieve efficient
supervised learning. A modified back-propagation algorithm
for such networks, which performs gradient descent in ``function space,''
is presented and its advantages are discussed. The benefits of the
suggested paradigm include faster learning and ease of interpretation
of the trained network.
_________________________________________________________________________
The following can be used to ftp the paper.
unix> ftp cheops.cis.ohio-state.edu # (or ftp 128.146.8.62)
Name (cheops.cis.ohio-state.edu:): anonymous
Password (cheops.cis.ohio-state.edu:anonymous): neuron
ftp> cd pub/neuroprose
ftp> type binary
ftp> get
(remote-file) mani.function-space.ps.Z
(local-file) mani.function-space.ps.Z
ftp> quit
unix> uncompress mani.function-space.ps.Z
unix> lpr -P(your_local_postscript_printer) mani.function-space.ps
More information about the Connectionists
mailing list