Spencer Greenberg

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We give the proof of a tight lower bound on the probability that a binomial random variable exceeds its expected value. The inequality plays an important role in a variety of contexts, including the analysis of relative deviation bounds in learning theory and generalization bounds for unbounded loss functions. 1 Motivation This paper presents a tight lower(More)
We present an extensive analysis of relative deviation bounds, including detailed proofs of two-sided inequalities and their implications. We also give detailed proofs of two-sided generalization bounds that hold in the general case of unbounded loss functions, under the assumption that a moment of the loss is bounded. These bounds are useful in the(More)
Study Objectives: To develop and test an easy to administer, conceptually sound, self-report fatigue state questionnaire, the Fatigue State Questionnaire (FSQ). A self-report study. The FSQ showed adequate internal consistency; Chronbach's alpha ranged from .73 to .82. Test-retest reliability after a ten-minute interval was also acceptable (r=.71). The FSQ(More)
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