This paper explores a novel framework for building regression models using association rules. The model consists of an ordered set of IF-THEN rules, where the rule consequent is t...
In this paper we present a family of models and learning algorithms that can simultaneously align and cluster sets of multidimensional curves measured on a discrete time grid. Our...
Bioinformatics aims at applying computer science methods to the wealth of data collected in a variety of experiments in life sciences (e.g. cell and molecular biology, biochemistry...
In this paper we aim at automatically adjusting the difficulty of computer games by clustering players into different types and supervised prediction of the type from short traces ...
Robust tracking of abrupt motion is a challenging task
in computer vision due to the large motion uncertainty. In
this paper, we propose a stochastic approximation Monte
Carlo (...