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Full-Text Articles in Physical Sciences and Mathematics
Multiple Learner Systems Using Resampling Methods, Binyun Xie
Multiple Learner Systems Using Resampling Methods, Binyun Xie
Computer Science Theses & Dissertations
The N-Learners Problem deals with combining a number of learners such that the resultant system is "better", under some criterion, than the best of the individual learners. We consider a system of probably approximately correct concept learners. Depending on the available information, there are several methods to make the composite system better than the best of the individual learners. If a sample and an oracle that generates data points (but, not their classification) is available, then we show that we can achieve arbitrary levels of the normalized confidence of the composite system if (a) a robust learning algorithm is available, …
Single Object Detection Using Multiple Sensors With Unknown Noise Distributions, Shaofen Chen
Single Object Detection Using Multiple Sensors With Unknown Noise Distributions, Shaofen Chen
Computer Science Theses & Dissertations
We consider the design of an object classification system that identifies single objects using a system of sensors; each sensor outputs a random vector, according to an unknown (noise) probability distribution, in response to a sensed object. We consider a special class of systems, called the linearly separable systems, where the error-free sensor outputs corresponding to distinct objects can be mapped into disjoint intervals on real line. Given a set of sensor outputs corresponding to known objects, we show that a detection rule αemp that approaches the correct rule with a high probability can be computed. We show …