Agnostic Learning of Geometric Patterns (Extended Abstract)
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) Sally A. Goldman Dept. of Computer Science Washington University St. Louis, MO 63130 [email protected] Stephen S. Kwek Dept. of Computer Science Washington University St. Louis, MO 63130 [email protected] Stephen D. Scott Dept. of Computer Science Washington University St. Louis, MO 63130 [email protected] Abstract Goldberg, Goldman, and Scott demonstrated how the problem of recognizing a landmark from a one-dimensional visual image can be mapped to that of learning a one-dimensional geometric pattern and gave a PAC algorithm to learn that class. We present an on-line agnostic learning algorithm for learning the class of one-dimensional geometric patterns. Since, when moving from the processed visual image to a one-dimensional pattern some key information is lost, we define a class of two-dimensional geometric patterns for which the important features from the visual image are incorporated in the geometric pattern, and show how to extend our agnostic learning algorithm to t..