Abstract. We present the Acyclic Bayesian Net Generator, a new approach to learn the structure of a Bayesian network using genetic algorithms. Due to the encoding mechanism, acycli...
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
Nowadays, path prediction is being extensively examined for use in the context of mobile and wireless computing towards more efficient network resource management schemes. Path pr...
This paper is about the work on user relevance feedback in image retrieval. We take this problem as a standard two-class pattern classification problem aiming at refining the retri...