CSE 291 : Learning Theory Fall 2006 Lecture 1 — Measure concentration
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چکیده
1.1 Concentration of measure: examples We start with some examples of “concentration of measure”. This phenomenon is very useful in analyzing machine learning algorithms and can be used to bound things like error probabilities. The first and the most standard of concentration results is for averages. It states that “the average of bounded independent random variables is tightly concentrated around its expectation”. 1.1.1 Example: coin tosses Suppose a coin of unknown bias p is tossed n times: X1, . . . , Xn ∈ {0, 1}. Then the average of the Xi is tightly concentrated around p. Specifically
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تاریخ انتشار 2006