A simple algorithmic explanation for the concentration of measure phenomenon
نویسنده
چکیده
We give an elementary algorithmic argument that sheds light on the concentration of measure phenomenon observed in the sum of independent random variables. Roughly speaking, we observe that without concentration of measure, it would be possible to predict the outcome of a fair coin toss with probability greater than 1/2. We use this idea to derive an alternative proof for a particular case of the ChernoffHoeffding bound.
منابع مشابه
An algorithmic proof of the Chernoff-Hoeffding bound
We provide a simple algorithmic argument to “explain” the concentration of measure phenomenon observed in the sum of independent random variables. Roughly speaking, we observe that without concentration of measure it would be possible to predict the outcome of a coin toss with probability greater than 1/2. We use this idea to derive an alternative proof of a Chernoff-Hoeffding bound for large d...
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تاریخ انتشار 2014