Autonomous Learning of Representations

Autor: Reinhold Haeb-Umbach, Barbara Hammer, Benjamin Paassen, Bassam Mokbel, Oliver Walter

Publikováno v: KI - Künstliche Intelligenz. 29:339-351

Besides the core learning algorithm itself, one major question in machine learning is how to best encode given training data such that the learning technology can efficiently learn based thereon and generalize to novel data. While classical approache

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e5fa576290e8c33a5972eba555512c08
https://doi.org/10.1007/s13218-015-0372-1

Visualizing the quality of dimensionality reduction

Autor: Wouter Lueks, Andrej Gisbrecht, Barbara Hammer, Bassam Mokbel

Publikováno v: Neurocomputing, 112, July, pp. 109-123
Neurocomputing, 112, 109-123
Neurocomputing, 112, 109-123. ELSEVIER SCIENCE BV

The growing number of dimensionality reduction methods available for data visualization has recently inspired the development of formal measures to evaluate the resulting low-dimensional representation independently from the methods' inherent criteri

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::45e850c2b8787cde89e2a7fd93c824ef
https://hdl.handle.net/11370/44afc56e-7db6-4683-86a1-74a2f0bf3b3f

Inferring Feature Relevances From Metric Learning

Autor: Bassam Mokbel, Alexander Schulz, Barbara Hammer, Michael Biehl

Publikováno v: Computational Intelligence, 2015 IEEE Symposium Series on, 1599-1606
STARTPAGE=1599;ENDPAGE=1606;TITLE=Computational Intelligence, 2015 IEEE Symposium Series on
SSCI

Powerful metric learning algorithms have been proposed in the last years which do not only greatly enhance the accuracy of distance-based classifiers and nearest neighbor database retrieval, but which also enable the interpretability of these operati

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d715fe36ff41aa085341b10d952e04ae
https://doi.org/10.1109/SSCI.2015.225

Towards Dimensionality Reduction for Smart Home Sensor Data

Autor: Bassam Mokbel, Alexander Schulz, Barbara Hammer, Thomas Martinetz, Thomas Villmann

Publikováno v: PUB-Publications at Bielefeld University

In this paper, we investigate in how far nonlinear dimensionality reduction (DR) techniques can be utilized to tackle particular challenges of sensor data from smart home environments. Smart homes often contain a large number of sensors of various ty

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::ce60d3e77e8117d805f6e176426d5491
https://pub.uni-bielefeld.de/record/2783369

How to Select an Example? A Comparison of Selection Strategies in Example-Based Learning

Autor: Sebastian Gross, Niels Pinkwart, Barbara Hammer, Bassam Mokbel

Publikováno v: Intelligent Tutoring Systems ISBN: 9783319072203
Intelligent Tutoring Systems

In this paper, we investigate an Intelligent Tutoring System (ITS) for Java programming that implements an example-based learning approach. The approach does not require an explicit formalization of the domain knowledge but automatically identifies a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c304e759310d4e2adf97e72257af9b97
https://doi.org/10.1007/978-3-319-07221-0_42