OPtimizing inductive bias

[Bruce Lambert]

HI folks,
         Recently Yoshua Bengio posted a note about using standard optimization
techniques to set tunable parameters to neural nets.  Dave Tcheng and I have
working on the same basic idea at a more general level for several years.
Rather than optimizing just networks, we have developed a framework for using
optimization to search a large inductive bias space defined by several
different types of algorithms (e.g., decision tree builders, nets, exemplar
based approaches, etc.).  Given the omnipresent necessity of tweaking biases to
get good performance, automation of the bias search seems very sensible.  A
couple of references to our work are given below.  We hope you find them useful
 
     -Bruce Lambert
      Department of Pharmacy Administration
      University of Illinois at Chicago
 
Tcheng, D., Lambert, B., Lu, S. C-Y., & Rendell, L.  (1989).  Building robust
  learning systems by combining induction and optimization.  In _Proc. 11th
  IJCAI_ (pp. 806-812).  San Mateo, CA:  Morgan Kaufman.
 
Tcheng, D., Lambert, B., Lu, S. C-Y, & Rendell, L.  (1991).  AIMS:  An adaptive
 interactive modelling system for supporting engineering decision making.  In
 L. Birnbaum & G. Collins (Eds.), _Machine learning:  Proceedings of the eighth
 international workshop_  (pp. 645-649).  San Mateo, CA:  Morgan Kaufman.