M. Aldridge, O. Johnson, и J. Scarlett. (2019)cite arxiv:1902.06002Comment: Survey paper, 140 pages, 19 figures. To be published in Foundations and Trends in Communications and Information Theory.
A. Genevay, L. Chizat, F. Bach, M. Cuturi, и G. Peyré. Proceedings of Machine Learning Research, том 89 из Proceedings of Machine Learning Research, стр. 1574--1583. PMLR, (16--18 Apr 2019)
J. Helton, T. Mai, и R. Speicher. (2015)cite arxiv:1511.05330Comment: We have undertaken a major revision, mainly for the sake of clarity and readability.
J. Negrea, M. Haghifam, G. Dziugaite, A. Khisti, и D. Roy. (2019)cite arxiv:1911.02151Comment: 23 pages, 1 figure. To appear in, Advances in Neural Information Processing Systems (33), 2019.
F. Nielsen, и R. Nock. (2013)cite arxiv:1309.3029Comment: 11 pages, two tables, no figure. Java(TM) code available online at http://www.informationgeometry.org/fDivergence/.
V. Papyan, J. Sulam, и M. Elad. (2017)cite arxiv:1707.06066Comment: This is the journal version of arXiv:1607.02005 and arXiv:1607.02009, accepted to IEEE Transactions on Signal Processing.
I. Sason, и S. Verdú. (2015)cite arxiv:1508.00335Comment: IEEE Trans. on Information Theory, vol. 62, no. 11, pp. 5973--6006, November 2016. This manuscript is identical to the journal paper, apart of some additional material which includes Sections III-C and IV-F, and three technical proofs.
D. Soudry, E. Hoffer, M. Nacson, S. Gunasekar, и N. Srebro. (2017)cite arxiv:1710.10345Comment: Final JMLR version, with improved discussions over v3. Main improvements in journal version over conference version (v2 appeared in ICLR): We proved the measure zero case for main theorem (with implications for the rates), and the multi-class case.
C. Wei, J. Lee, Q. Liu, и T. Ma. (2018)cite arxiv:1810.05369Comment: version 2: title changed from originally Ön the Margin Theory of Feedforward Neural Networks". Substantial changes from old version of paper, including a new lower bound on NTK sample complexity version 3: reorganized NTK lower bound proof.