141 citations · 597 across the 22 of their papers we have counts for
Showing 2012Show all
3 papers · 1 filter
cs.LG2012★ 110 cited
Efficient Monte Carlo Methods for Multi-Dimensional Learning with Classifier Chains
Jesse Read, Luca Martino, David Luengo
Multi-dimensional classification (MDC) is the supervised learning problem where an instance is associated with multiple classes, rather than with a single class, as in traditional…
stat.CO2012★ 96 cited
Improved Adaptive Rejection Metropolis Sampling Algorithms
Luca Martino, Jesse Read, David Luengo
Markov Chain Monte Carlo (MCMC) methods, such as the Metropolis-Hastings (MH) algorithm, are widely used for Bayesian inference. One of the most important issues for any MCMC metho…
stat.CO2012★ 45 cited
On the flexibility of the design of Multiple Try Metropolis schemes
Luca Martino, Jesse Read
The Multiple Try Metropolis (MTM) method is a generalization of the classical Metropolis-Hastings algorithm in which the next state of the chain is chosen among a set of samples, a…