In this paper we introduce a novel optimization framework for hierarchical data clustering and apply it to the problem of unsupervised texture segmentation. The proposed objective...
This paper studies the problem of categorical data clustering, especially for transactional data characterized by high dimensionality and large volume. Starting from a heuristic m...
The present paper mainly studies the expected teaching time of memoryless randomized learners without feedback. First, a characterization of optimal randomized learners is provided...
—The synchronous model of computation together with a suitable execution platform facilitates system-level timing predictability. This paper introduces an algebraic framework for...
Michael Mendler, Reinhard von Hanxleden, Claus Tra...
We are interested in automatically proving safety properties of infinite state systems. We present a technique for invariant synthesis which can be incorporated in backward reacha...