Sampler for Composition Ratio by Markov Chain Monte Carlo

06/16/2019
by   Yachiko Obara, et al.
0

Invention involves combination, or more precisely, ratios of composition. According to Thomas Edison, "Genius is one percent inspiration and 99 percent perspiration" is an example. In many situations, researchers and inventors already have a variety of data and manage to create something new by using it, but the key problem is how to select and combine knowledge. In this paper, we propose a new Markov chain Monte Carlo (MCMC) algorithm to generate composition ratios, nonnegative-integer-valued vectors with two properties: (i) the sum of the elements of each vector is constant, and (ii) only a small number of elements is nonzero. These constraints make it difficult for existing MCMC algorithms to sample composition ratios. The key points of our approach are (1) designing an appropriate target distribution by using a condition on the number of nonzero elements, and (2) changing values only between a certain pair of elements in each iteration. Through an experiment on creating a new cocktail, we show that the combination of the proposed method with supervised learning can solve a creative problem.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/15/2017

Metropolis Sampling

Monte Carlo (MC) sampling methods are widely applied in Bayesian inferen...
research
12/07/2020

Ratio of counts vs ratio of rates in Poisson processes

The often debated issue of `ratios of small numbers of events' is approa...
research
05/23/2020

Most Likely Optimal Subsampled Markov Chain Monte Carlo

Markov Chain Monte Carlo (MCMC) requires to evaluate the full data likel...
research
03/20/2020

Multiple projection MCMC algorithms on submanifolds

We propose new Markov Chain Monte Carlo algorithms to sample probability...
research
07/26/2023

MCMC-Correction of Score-Based Diffusion Models for Model Composition

Diffusion models can be parameterised in terms of either a score or an e...
research
12/01/2021

A quantum parallel Markov chain Monte Carlo

We propose a novel quantum computing strategy for parallel MCMC algorith...
research
06/29/2021

Contamination mapping in Bangladesh using a multivariate spatial Bayesian model for left-censored data

Arsenic (As) and other toxic elements contamination of groundwater in Ba...

Please sign up or login with your details

Forgot password? Click here to reset