This paper describes a parameter estimation method for multi-label classification that does not rely on approximate inference. It is known that multi-label classification involvin...
Abstract. We all highly depend and rely on the trustworthiness of information and services provided by various parties and institutions. Reputation systems are one possibility to s...
Andreas Gutscher, Jessica Heesen, Oliver Siemoneit
We present a novel probabilistic multiple cause model for binary observations. In contrast to other approaches, the model is linear and it infers reasons behind both observed and ...
In many pattern recognition/classification problem the true class conditional model and class probabilities are approximated for reasons of reducing complexity and/or of statistic...
Abstract: We define events so as to reduce the number of events and decision variables needed for modeling batchscheduling problems such as described in [Westenberger and Kallrath ...