In this work, we propose adaptive frequency-domain biased estimation algorithms with mechanisms to automatically adjust the shrinkage factors. The proposed estimation algorithms i...
Clustering is a basic task in a variety of machine learning applications. Partitioning a set of input vectors into compact, wellseparated subsets can be severely affected by the p...
Pedro A. Forero, Vassilis Kekatos, Georgios B. Gia...
Two sets of linguistic features are developed: The first one to estimate if a single step in a dialogue between a human being and a machine is successful or not. The second set to...
Stefan Steidl, Christian Hacker, Christine Ruff, A...
We consider principal component analysis (PCA) in decomposable Gaussian graphical models. We exploit the prior information in these models in order to distribute its computation. ...
This paper seeks to increase the efficiency of background subtraction algorithms for motion detection. Our method uses a quadtree-base hierarchical framework that samples a small ...