Abstract: Many distributed optimization algorithms critically depend on careful step-size tuning to ensure stability and achieve fast convergence. In this work, we address this limitation in the ...
Abstract: Markov chain Monte Carlo (MCMC) algorithms are widely used in Bayesian inference to compute the posterior distribution of complex models, facilitating sampling from probability distributions ...
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