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. Developing the ability to recognize a landmark from a visual image of a robot'scurrent location is a fundamental problem in robotics. We describe a way in which the landmarkmatching problem can be mapped to that of learning a one-dimensional geometric pattern. Thefirst contribution of our work is an efficient noise-tolerant algorithm (designed using the statisticalquery model) to PAC-learn the class of one-dimensional geometric patterns. The second contributionof our work is an empirical ...

A Theoretical and Empirical Study of a Noise-Tolerant Algorithm to Learn Geometric Patterns