Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pa...
Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Ro...
Abstract. In this paper we focus on explaining to humans the behavior of autonomous agents, i.e., explainable agents. Explainable agents are useful for many reasons including scena...
Joost Broekens, Maaike Harbers, Koen V. Hindriks, ...
The full deployment of service robots in daily activities will require the robot to adapt to the needs of non-expert users, particularly, to learn how to perform new tasks from “...
Ana C. Tenorio-Gonzalez, Eduardo F. Morales, Luis ...
This paper addresses the supervised learning in which the class membership of training data are subject to uncertainty. This problem is tackled in the framework of the Dempster-Sha...
We present a novel approach for extracting cluttered objects based on their morphological properties1 . Specifically, we address the problem of untangling C. elegans clusters in h...
Tammy Riklin Raviv, Vebjorn Ljosa, Annie L. Conery...