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.
H. Zhang, Y. Dauphin, и T. Ma. (2019)cite arxiv:1901.09321Comment: Accepted for publication at ICLR 2019; see https://openreview.net/forum?id=H1gsz30cKX.
J. Yosinski, J. Clune, Y. Bengio, и H. Lipson. (2014)cite arxiv:1411.1792Comment: To appear in Advances in Neural Information Processing Systems 27 (NIPS 2014).
O. Yadan, K. Adams, Y. Taigman, и M. Ranzato. (2013)cite arxiv:1312.5853Comment: Machine Learning, Deep Learning, Convolutional Networks, Computer Vision, GPU, CUDA.
R. Straeten, T. Mens, J. Simmonds, и V. Jonckers. UML 2003 – The Unified Modeling Language, том 2863 из Lecture Notes in Computer Science, стр. 326--340. Springer, (2003)
H. Spieker, A. Gotlieb, D. Marijan, и M. Mossige. (2018)cite arxiv:1811.04122Comment: Spieker, H., Gotlieb, A., Marijan, D., & Mossige, M. (2017). Reinforcement Learning for Automatic Test Case Prioritization and Selection in Continuous Integration. In Proceedings of 26th International Symposium on Software Testing and Analysis (ISSTA'17) (pp. 12--22). ACM.
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein и 2 other автор(ы). (2014)cite arxiv:1409.0575Comment: 43 pages, 16 figures. v3 includes additional comparisons with PASCAL VOC (per-category comparisons in Table 3, distribution of localization difficulty in Fig 16), a list of queries used for obtaining object detection images (Appendix C), and some additional references.
A. Razavian, H. Azizpour, J. Sullivan, и 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.
D. Povey, X. Zhang, и S. Khudanpur. (2014)cite arxiv:1410.7455Comment: Accepted as workshop contribution to ICLR 2015. 12 pages plus 16 pages of appendices, International Conference on Learning Representations (ICLR): Workshop track, 2015. 2 sets of minor fixes post-publication..
B. Motik. Proceedings of the 18th International Conference on Conceptual Structures (ICCS 2010), том 6208 из Lecture Notes in Computer Science, стр. 10-12. Springer, (2010)
J. Metzger, F. Ber, и A. Napoli. Proceedings of the 11th International Conference on Conceptual Structures (ICCS 2003), том 2746 из Lecture Notes in Computer Science, стр. 215-228. Springer, (2003)
C. Ma, V. Smith, M. Jaggi, M. Jordan, P. Richtárik, и M. Takáč. (2015)cite arxiv:1502.03508Comment: ICML 2015: JMLR W&CP volume37, Proceedings of The 32nd International Conference on Machine Learning, pp. 1973-1982.
H. Li, Z. Xu, G. Taylor, C. Studer, и T. Goldstein. (2017)cite arxiv:1712.09913Comment: NIPS 2018 (extended version, 10.5 pages), code is available at https://github.com/tomgoldstein/loss-landscape.