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An ADMM Algorithm for a Class of Total Variation Regularized Estimation Problems
Signal processing algorithms stochastic parameters parameter estimation
2015/7/9
We present an alternating augmented Lagrangian method for convex optimization problems where the cost function is the sum of two terms, one that is separable in the variable blocks, and a second that ...
Quantitative bounds for Markov chain convergence: Wasserstein and total variation distances
convergence rate coupling Gibbs sampler iterated random functions local
2011/3/24
We present a framework for obtaining explicit bounds on the rate of convergence to equilibrium of a Markov chain on a general state space, with respect to both total variation and Wasserstein distance...
A Lower Bound on Arbitrary f--Divergences in Terms of the Total Variation
Lower Bound Arbitrary f--Divergences Total Variation
2010/3/19
An important tool to quantify the likeness of two probability measures
are f–divergences, which have seen widespread application in statistics
and information theory. An example is the total variati...