The original Parameter-Less Self-Organising Map (PLSOM) algorithm was introduced as a solution to the problems the Self-Organising Map (SOM) encounters when dealing with certain ty...
Abstract Consider a random graph model where each possible edge e is present independently with some probability pe. Given these probabilities, we want to build a large/heavy match...
We consider the problem of finding a ranking of a set of elements that is "closest to" a given set of input rankings of the elements; more precisely, we want to find a p...
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
We consider the problem of performing learning and inference in a large scale knowledge base containing imperfect knowledge with incomplete coverage. We show that a soft inference...