We present an algorithm, called the offset tree, for learning in situations where a loss associated with different decisions is not known, but was randomly probed. The algorithm i...
XML Schema Definitions (XSDs) can be adequately abstracted by the single-type regular tree languages. It is wellknown, that these form a strict subclass of the robust class of re...
Wouter Gelade, Tomasz Idziaszek, Wim Martens, Fran...
We propose two new online methods for estimating the size of a backtracking search tree. The first method is based on a weighted sample of the branches visited by chronological ba...
In this paper, we present a new algorithm that integrates recent advances in solving continuous bandit problems with sample-based rollout methods for planning in Markov Decision P...
Christopher R. Mansley, Ari Weinstein, Michael L. ...
Abstract. This paper presents a neural network tree regression system with dynamic optimization of input variable transformations and post-training optimization. The decision tree ...
Miroslaw Kordos, Marcin Blachnik, Tadeusz Wieczore...