3 papers
cs.AI2013
Second Order Probabilities for Uncertain and Conflicting Evidence
Gerhard Paaß
In this paper the elicitation of probabilities from human experts is considered as a measurement process, which may be disturbed by random 'measurement noise'. Using Bayesian conce…
cs.AI2013
Integrating Probabilistic Rules into Neural Networks: A Stochastic EM Learning Algorithm
Gerhard Paass
The EM-algorithm is a general procedure to get maximum likelihood estimates if part of the observations on the variables of a network are missing. In this paper a stochastic versio…
cs.AI2013
MESA: Maximum Entropy by Simulated Annealing
Gerhard Paaß
Probabilistic reasoning systems combine different probabilistic rules and probabilistic facts to arrive at the desired probability values of consequences. In this paper we describe…