Abstract. Ensemble methods are popular learning methods that usually increase the predictive accuracy of a classifier though at the cost of interpretability and insight in the deci...
The problem of learning forest-structured discrete graphical models from i.i.d. samples is considered. An algorithm based on pruning of the Chow-Liu tree through adaptive threshol...
Vincent Y. F. Tan, Animashree Anandkumar, Alan S. ...
To achieve high accuracy while lowering false alarm rates are major challenges in designing an intrusion detection system. In addressing this issue, this paper proposes an ensembl...
Anazida Zainal, Mohd Aizaini Maarof, Siti Mariyam ...
This paper proposes a forest-based tree sequence to string translation model for syntaxbased statistical machine translation, which automatically learns tree sequence to string tr...
Hui Zhang, Min Zhang, Haizhou Li, AiTi Aw, Chew Li...
In this paper we present decomposable priors, a family of priors over structure and parameters of tree belief nets for which Bayesian learning with complete observations is tracta...