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Why is Lasso penalty equivalent to the double exponential (Laplace) prior?

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I have read in a number of references that the Lasso estimate for the regression parameter vector $B$ is equivalent to the posterior mode of $B$ in which the prior distribution for each $B_i$ is a double exponential distribution (also known as Laplace distribution).

I have been trying to prove this, can someone flesh out the details?


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