Preprint on Inductive Transfer in ANNs available

[Danny L. Silver]

A preprint of the article:                   
  
"Parallel Transfer of Task Knowledge Using Dynamic Learning Rates Based
on a Measure of Relatedness"
  
can be found at:    http://www.csd.uwo.ca/~dsilver/CSetaMTL.ps.Z
  
The article has been accepted for publication in the Connection Science
special issue on "Transfer in Inductive Systems" due out this fall.
  
	
			  ABSTRACT

With a distinction made between two forms of task knowledge transfer,
{\em representational} and {\em functional}, $\eta$MTL, a modified
version of the MTL method of functional (parallel) transfer, is introduced.
The $\eta$MTL method employs a separate learning rate, $\eta_k$, for each
task output node $k$. $\eta_k$ varies as a function of a measure of
relatedness, $R_k$, between the $k$th task and the primary task of interest.
Results of experiments demonstrate the ability of $\eta$MTL to dynamically 
select the most related source task(s) for the functional transfer of prior 
domain knowledge.  The $\eta$MTL method of learning is nearly equivalent to
standard MTL when all parallel tasks are sufficiently related to the
primary task, and is similar to single task learning when none of the
parallel tasks are related to the primary task. 


If you have any difficulties with transmission or wish to receive the article
by another means please contact me as below.
  
. Danny
-- 
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=  Daniel L. Silver    University of Western Ontario, London, Canada    =
=                      N6A 3K7 - Dept. of Comp. Sci.                    =
=  dsilver at csd.uwo.ca  H: (902)582-7558   O: (902)494-1813              =
=  WWW home page ....  http://www.csd.uwo.ca/~dsilver                   =
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