The increasing number of knowledge-based systems that build on a Bayesian belief network or influence diagram acknowledge the usefulness of these frameworks for addressing complex...
In this paper, the problem of time series prediction is studied. A Bayesian procedure based on Gaussian process models using a nonstationary covariance function is proposed. Exper...
Probability trees (or Probability Estimation Trees, PET’s) are decision trees with probability distributions in the leaves. Several alternative approaches for learning probabilit...
Daan Fierens, Jan Ramon, Hendrik Blockeel, Maurice...
The problem is sequence prediction in the following setting. A sequence x1, . . . , xn, . . . of discrete-valued observations is generated according to some unknown probabilistic ...
Society has grown to rely on Internet services, and the number of Internet users increases every day. As more and more users become connected to the network, the window of opportu...