149 citations · 529 across the 35 of their papers we have counts for
Showing 2013Show all
3 papers · 1 filter
stat.ML2013★ 6 cited
Sequential Monte Carlo Bandits
Michael Cherkassky, Luke Bornn
In this paper we propose a flexible and efficient framework for handling multi-armed bandits, combining sequential Monte Carlo algorithms with hierarchical Bayesian modeling techni…
stat.CO2013
PAWL-Forced Simulated Tempering
Luke Bornn
In this short note, we show how the parallel adaptive Wang-Landau (PAWL) algorithm of Bornn et al. (2013) can be used to automate and improve simulated tempering algorithms. While…
cs.LG2013★ 1 cited
Herded Gibbs Sampling
Luke Bornn, Yutian Chen, Nando de Freitas +3
The Gibbs sampler is one of the most popular algorithms for inference in statistical models. In this paper, we introduce a herding variant of this algorithm, called herded Gibbs, t…