The problem of obtaining the maximum a posteriori (map) estimate of a discrete random field is of fundamental importance in many areas of Computer Science. In this work, we build ...
There is a range of potential applications of Machine Learning where it would be more useful to predict the probability distribution for a variable rather than simply the most lik...
Michael Carney, Padraig Cunningham, Jim Dowling, C...
We propose a new kernel function for attributed molecular graphs, which is based on the idea of computing an optimal assignment from the atoms of one molecule to those of another ...
The conditional distribution of a discrete variable y, given another discrete variable x, is often specified by assigning one multinomial distribution to each state of x. The cost...
Learning agents can improve performance cooperating with other agents, particularly learning agents forming a committee outperform individual agents. This "ensemble effect&qu...