Publication Details
Title: Bumptrees for Efficient Function, Constraint, and Classification Learning
Author: S. M. Omohundro
Group: ICSI Technical Reports
Date: January 1991
PDF: ftp://ftp.icsi.berkeley.edu/pub/techreports/1991/tr-91-009.pdf
Overview:
A new class of data structures called "bumptrees" is described. These structures are useful for efficiently implementing a number of neural network related operations. An empirical comparison with radial basis functions is presented on a robot arm mapping learning task. Applications to density estimation, classification, and constraint representation and learning are also outlined.
Bibliographic Information:
ICSI Technical Report TR-91-009
Bibliographic Reference:
S. M. Omohundro. Bumptrees for Efficient Function, Constraint, and Classification Learning. ICSI Technical Report TR-91-009, January 1991
Author: S. M. Omohundro
Group: ICSI Technical Reports
Date: January 1991
PDF: ftp://ftp.icsi.berkeley.edu/pub/techreports/1991/tr-91-009.pdf
Overview:
A new class of data structures called "bumptrees" is described. These structures are useful for efficiently implementing a number of neural network related operations. An empirical comparison with radial basis functions is presented on a robot arm mapping learning task. Applications to density estimation, classification, and constraint representation and learning are also outlined.
Bibliographic Information:
ICSI Technical Report TR-91-009
Bibliographic Reference:
S. M. Omohundro. Bumptrees for Efficient Function, Constraint, and Classification Learning. ICSI Technical Report TR-91-009, January 1991