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Everything about Chernoff bound
Exponentially decreasing bounds on tail distributions of random variables
In probability theory, a Chernoff bound is an exponentially decreasing upper bound on the tail of a random variable based on its moment generating function. The minimum of all such exponential bounds forms the Chernoff or Chernoff-Cramér bound, which may decay faster than exponential. It is especially useful for sums of independent random variables, such as sums of Bernoulli random variables. Wikipedia →
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- Read the overview: Chernoff boundA 5-minute orientation
- Pick up a classic book: Algorithm Design and ApplicationsThe most-reprinted book on the subject
- Read the landmark paper: Data-Driven Anomaly Detection in Robots using Matrix Chernoff BoundsCited 0 times
- Go sideways: Hoeffding's inequalityA closely related topic
- Go sideways: Concentration inequalityA closely related topic
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đź“š Books worth reading
Algorithm Design and ApplicationsMichael T. Goodrich, Roberto Tamassia · 2014
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