Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...
Conjunctive queries play an important role as an expressive query language for Description Logics (DLs). Although modern DLs usually provide for transitive roles, conjunctive quer...
Birte Glimm, Ian Horrocks, Carsten Lutz, Ulrike Sa...
The martingale framework for detecting changes in data stream, currently only applicable to labeled data, is extended here to unlabeled data using clustering concept. The one-pass...
Some Statistical Software Testing approaches rely on sampling the feasible paths in the control flow graph of the program; the difficulty comes from the tiny ratio of feasible p...
We describe an approach to extract attribute-value pairs from product descriptions. This allows us to represent products as sets of such attribute-value pairs to augment product d...
Katharina Probst, Rayid Ghani, Marko Krema, Andrew...
We propose a novel approach to self-regenerating systems which require continuous operation, such as security surveillance. For that aim we introduce HADES, a self-regenerating co...
Learning capabilities of computer systems still lag far behind biological systems. One of the reasons can be seen in the inefficient re-use of control knowledge acquired over the...
This paper develops a statistical inference approach, Bayesian Tensor Inference, for style transformation between photo images and sketch images of human faces. Motivated by the r...
We introduce relational grams (r-grams). They upgrade n-grams for modeling relational sequences of atoms. As n-grams, r-grams are based on smoothed n-th order Markov chains. Smoot...