—Randomized learning methods (i.e., Forests or Ferns) have shown excellent capabilities for various computer vision applications. However, it was shown that the tree structure in...
Martin Godec, Christian Leistner, Amir Saffari, Ho...
This paper investigates a novel model-free reinforcement learning architecture, the Natural Actor-Critic. The actor updates are based on stochastic policy gradients employing Amari...
It has been observed that traditional decision trees produce poor probability estimates. In many applications, however, a probability estimation tree (PET) with accurate probabilit...
Abstract. This paper studies the properties and performance of models for estimating local probability distributions which are used as components of larger probabilistic systems â€...
Kristina Toutanova, Mark Mitchell, Christopher D. ...
This paper presents an investigation into the combination of different classifiers for toxicity prediction. These classification methods involved in generating classifiers for comb...