Andre Wibisono

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math.ST2024

Fast Convergence of $Φ$ -Divergence Along the Unadjusted Langevin Algorithm and Proximal Sampler

Siddharth Mitra, Andre Wibisono

We study the mixing time of two popular discrete-time Markov chains in continuous space, the Unadjusted Langevin Algorithm and the Proximal Sampler, which are discretizations of th…

math.ST2024

Characterizing Dependence of Samples along the Langevin Dynamics and Algorithms via Contraction of $Φ$ -Mutual Information

Jiaming Liang, Siddharth Mitra, Andre Wibisono

The mixing time of a Markov chain determines how fast the iterates of the Markov chain converge to the stationary distribution; however, it does not control the dependencies betwee…

Fast Convergence of Φ-Divergence Along the Unadjusted Langevin Algorithm and Proximal Sampler

Characterizing Dependence of Samples along the Langevin Dynamics and Algorithms via Contraction of Φ-Mutual Information

Fast Convergence of $Φ$ -Divergence Along the Unadjusted Langevin Algorithm and Proximal Sampler

Characterizing Dependence of Samples along the Langevin Dynamics and Algorithms via Contraction of $Φ$ -Mutual Information