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Abstract: AN EMPIRICAL APPROACH TO REAL-VALUED MULTIPLE-INSTANCE CLASSIFICATIONS by Robert A. Amar ADVISOR: Professor Sally A. Goldman August, 2000 St. Louis, Missouri The model of multiple-instance learning has recently arisen in the machine learning community as a new and important setting for several real-world problems, most notably drug design and discovery. However, most work, both theoretical and empirical, has been aimed at classifying target objects in a Boolean, or binary, fashion. Often we ... (Update)
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BibTeX entry: (Update)
@misc{ amar-empirical,
author = "Robert A. Amar",
title = "An Empirical Approach To Real-Valued Multiple-Instance Classifications",
url = "citeseer.ist.psu.edu/amar00empirical.html" }
Citations (may not include all citations):79 Solving the multiple-instance problem with axis-parallel rec.. - Dietterich, Lathrop et al. - 1997
27 A framework for multiple-instance learning - Maron, Lozano-Prez - 1998
22 On learning from multi-instance examples: Empirical evaluati.. - Auer - 1997
17 Learning from ambiguity - Maron - 1998
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