This paper introduces a novel stochastic approach to image denoising using an adaptive Monte Carlo scheme. Random samples are generated from the image field using a spatially-adap...
Alexander Wong, Akshaya Kumar Mishra, Paul W. Fieg...
A methodology for hierarchicalstatistical circuit characterization which does not rely upon circuit-level Monte Carlo simulation is presented. The methodology uses principalcompon...
Eric Felt, Stefano Zanella, Carlo Guardiani, Alber...
Many formal models of cognition implicitly use subjective probability distributions to capture the assumptions of human learners. Most applications of these models determine these...
We present an iterative Markov chain Monte Carlo algorithm for computing reference priors and minimax risk for general parametric families. Our approach uses MCMC techniques based...
Decisionand optimizationproblemsinvolvinggraphsarise in manyareas of artificial intelligence, including probabilistic networks, robot navigation, and network design. Manysuch prob...