In this paper, we study a maximum likelihood estimation (MLE) approach to preference aggregation and voting when the set of alternatives has a multi-issue structure, and the voter...
We present an efficient and accurate object tracking algorithm based on the concept of graph cut segmentation. The ability to track visible objects in real-time provides an inval...
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
We investigate the problem of learning action effects in partially observable STRIPS planning domains. Our approach is based on a voted kernel perceptron learning model, where act...
We address the problem of autonomously learning controllers for visioncapable mobile robots. We extend McCallum's (1995) Nearest-Sequence Memory algorithm to allow for genera...
Viktor Zhumatiy, Faustino J. Gomez, Marcus Hutter,...