One of the most formidable issues of RL application to real robot tasks is how to find a suitable state space, and this has been much more serious since recent robots tends to hav...
This paper analyses the computational complexity and stability of an online algorithm recently proposed for learning rotations. The proposed algorithm involves multiplicative upda...
Bayesian methods for visual tracking model the likelihood of image measurements conditioned on a tracking hypothesis. Image measurements may, for example, correspond to various fi...
In a data streaming setting, data points are observed one by one. The concepts to be learned from the data points may change infinitely often as the data is streaming. In this pap...
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...