In this paper we propose a new approach for semi-supervised structured output learning. Our approach uses relaxed labeling on unlabeled data to deal with the combinatorial nature ...
Paramveer S. Dhillon, S. Sathiya Keerthi, Kedar Be...
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
The application of patterns is used as a foundation for many central design decisions in software architecture, but because of the informal nature of patterns, these design decisi...
Uwe Zdun, Paris Avgeriou, Carsten Hentrich, Schahr...
One of the challenges faced by network management systems is the increasing need for consistent management of physical network equipment. We propose a solution where equipment is m...
Krzysztof Miksa, Marek Kasztelnik, Pawel Sabina, T...
The second ACES-MB workshop brought together researchers and practitioners interested in model-based software engineering for realtime embedded systems, with a particular focus on ...
Stefan Van Baelen, Thomas Weigert, Ileana Ober, Hu...