This paper introduces a novel machine learning model called multiple instance ranking (MIRank) that enables ranking to be performed in a multiple instance learning setting. The mo...
Charles Bergeron, Jed Zaretzki, Curt M. Breneman, ...
Feature selection, as a preprocessing step to machine learning, has been effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and improvin...
Although Bayesian model averaging is theoretically the optimal method for combining learned models, it has seen very little use in machine learning. In this paper we study its app...
We report the results of a study on topic spotting in conversational speech. Using a machine learning approach, we build classifiers that accept an audio file of conversational hu...
Kary Myers, Michael J. Kearns, Satinder P. Singh, ...
In recent years manifold methods have attracted a considerable amount of attention in machine learning. However most algorithms in that class may be termed “manifold-motivatedâ€...