Concentration of Measure from Eigenvalue Bounds
نویسنده
چکیده
Concentration of Measure refers to a techinque in probability for proving that certain random variables are unlikely to take values too much larger or smaller than their median. For example, consider the sum of d independent and uniformly chosen ±1 variables, x1, . . . , xd. The mean of the sum is obviously 0, and the symmetry of the distributions tells us that the median is 0 as well. The Chernoff bound tells us that for every t > 0,
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