Processing Short-Term and Long-Term Information With a Combination of Polynomial Approximation Techniques and Time-Delay Neural Networks. - Erich Fuchs; Christian Gruber; Tobias Reitmaier; Bernhard Sick (IEEE Trans. Neural Networks, 2009)

Active classifier training with the 3DS strategy. - Tobias Reitmaier; Bernhard Sick (CIDM, 2011)

Let us know your decision: Pool-based active training of a generative classifier with the selection strategy 4DS. - Tobias Reitmaier; Bernhard Sick (Inf. Sci., 2013)

Aktives Lernen für Klassifikationsprobleme unter der Nutzung von Strukturinformationen. - Tobias Reitmaier (Ausgezeichnete Informatikdissertationen, 2015)

A New Vision of Collaborative Active Learning. - Adrian Calma; Tobias Reitmaier; Bernhard Sick; Paul Lukowicz (CoRR, 2015)

Transductive active learning - A new semi-supervised learning approach based on iteratively refined generative models to capture structure in data. - Tobias Reitmaier; Adrian Calma; Bernhard Sick (Inf. Sci., 2015)

The responsibility weighted Mahalanobis kernel for semi-supervised training of support vector machines for classification. - Tobias Reitmaier; Bernhard Sick (Inf. Sci., 2015)

Aktives Lernen für Klassifikationsprobleme unter der Nutzung von Strukturinformationen. - Tobias Reitmaier (2015)

Lifelong Learning and Collaboration of Smart Technical Systems in Open-Ended Environments - Opportunistic Collaborative Interactive Learning. - Gernot Bahle; Adrian Calma; Jan Marco Leimeister; Paul Lukowicz; Sarah Oeste-Reiss; Tobias Reitmaier; Albrecht Schmidt 001; Bernhard Sick; Gerd Stumme; Katharina Anna Zweig (ICAC, 2016)

Resp-kNN: A probabilistic k-nearest neighbor classifier for sparsely labeled data. - Adrian Calma; Tobias Reitmaier; Bernhard Sick (IJCNN, 2016)

Semi-supervised active learning for support vector machines: A novel approach that exploits structure information in data. - Adrian Calma; Tobias Reitmaier; Bernhard Sick (Inf. Sci., 2018)