Joel Ratsaby

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1 INTRODUCTION We investigate the tradeoff between labeled The classical problem of learning a classification rule and unlabeled sample complexities in learning can be stated as follows: patterns from classes " 1 " and a classification rule for a parametric two-class " 2 " (or " states of nature ") appear with probabilities problem. In the problem(More)
1 Introduction One of the main problems in machine learning and statistical inference is selecting an appropriate model by which a set of data can be explained. In the absense of any structured prior information aa to the data generating mechanism, one is often forced to consider a range of models, attempting to select the model which best explains the(More)
Shannon's theory of information stands on a probabilistic representation of events that convey information, e.g., sending messages over a communication channel. Kolmogorov argues that information is a more fundamental concept which exists also in problems with no underlying stochastic model, for instance, the information contained in an algorithm or in the(More)