Notice: Undefined variable: noHierarchyInTitle in /var/www/template.inc on line 17 Lundell, Jared's Publications (detailed list) - NNML Laboratory

This page contains the titles and abstracts of papers written by author Lundell, Jared, a member of the BYU Neural Networks and Machine Learning (NNML) Research Group. Postscript files are available for most papers. A more concise list is available.

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A Data-dependent Distance Measure for Transductive Instance-based Learning

Authors: Jared Lundell and Dan Ventura
Abstract: We consider learning in a transductive setting using instance-based learning (k-NN) and present a method for constructing a data-dependent distance “metric” using both labeled training data as well as available unlabeled data (that is to be classified by the model). This new data-driven measure of distance is empirically studied in the context of various instance-based models and is shown to reduce error (compared to traditional models) under certain learning conditions. Generalizations and improvements are suggested.
Reference: In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, pages 2825–2830, October 2007.
BibTeX:
@inproceedings{lundell.smc07,
author = {Lundell, Jared and Ventura, Dan},
title = {A Data-dependent Distance Measure for Transductive Instance-based Learning},
booktitle = {Proceedings of the {IEEE} International Conference on Systems, Man and Cybernetics},
pages = {2825--2830},
month = {October},
year = {2007},
}
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