We extend the description logic EL++ with reflexive roles
and range restrictions, and show that subsumption remains tractable if
a certain syntactic restriction is adopted. We also show that subsumption
becomes PSpace-hard (resp. undecidable) if this restriction is weakened
(resp. dropped). Additionally, we prove that tractability is lost when
symmetric roles are added: in this case, subsumption becomes ExpTime-
hard
r. Kurt Bollacker is a computer scientist with a research background in the areas of machine learning, digital libraries, semantic networks, and electro-cardiographic modeling. He received a Ph.D. in Computer Engineering from The University Of Texas At Austin, was co-creator of the Citeseer research tool as a visiting researcher at the NEC Research Institute, was the technical director of the Internet Archive, and a biomedical research engineer at the Duke University Medical Center. He is currently pursuing research into long term digital archiving as the Digital Research Director at the Long Now Foundation, and is a scientist at Metaweb Technologies.
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D. Kingma, und J. Ba. (2014)cite arxiv:1412.6980Comment: Published as a conference paper at the 3rd International Conference for Learning Representations, San Diego, 2015.
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B. Baker, O. Gupta, R. Raskar, und N. Naik. (2017)cite arxiv:1705.10823Comment: Submitted to International Conference on Learning Representations, (2018).
H. Zhang, Y. Dauphin, und T. Ma. (2019)cite arxiv:1901.09321Comment: Accepted for publication at ICLR 2019; see https://openreview.net/forum?id=H1gsz30cKX.
H. Li, Z. Xu, G. Taylor, C. Studer, und T. Goldstein. (2017)cite arxiv:1712.09913Comment: NIPS 2018 (extended version, 10.5 pages), code is available at https://github.com/tomgoldstein/loss-landscape.
J. Yosinski, J. Clune, Y. Bengio, und H. Lipson. (2014)cite arxiv:1411.1792Comment: To appear in Advances in Neural Information Processing Systems 27 (NIPS 2014).
A. Razavian, H. Azizpour, J. Sullivan, und S. Carlsson. (2014)cite arxiv:1403.6382Comment: version 3 revisions: 1)Added results using feature processing and data augmentation 2)Referring to most recent efforts of using CNN for different visual recognition tasks 3) updated text/caption.
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