Monte Carlo Tree Search is a recent algorithm that achieves more and more successes in various domains. We propose an improvement of the Monte Carlo part of the algorithm by modify...
Abstract. This paper is concerned with generalization issues for a decision tree learner for structured data called Alkemy. Motivated by error bounds established in statistical lea...
Computer experiments often require dense sweeps over input parameters to obtain a qualitative understanding of their response. Such sweeps can be prohibitively expensive, and are ...
Robert B. Gramacy, Herbert K. H. Lee, William G. M...
In this paper we propose PARTfs which adopts a supervised machine learning algorithm, namely partial decision trees, as a method for feature subset selection. In particular, it is...
We present an algorithm that induces a class of models with thin junction trees--models that are characterized by an upper bound on the size of the maximal cliques of their triang...