J. Fadili, G. Garrigos, J. Malick, und G. Peyré. Proceedings of Machine Learning Research, Volume 89 von Proceedings of Machine Learning Research, Seite 1236--1244. PMLR, (16--18 Apr 2019)
G. Louppe, J. Hermans, und K. Cranmer. Proceedings of Machine Learning Research, Volume 89 von Proceedings of Machine Learning Research, Seite 1438--1447. PMLR, (16--18 Apr 2019)
A. Genevay, L. Chizat, F. Bach, M. Cuturi, und G. Peyré. Proceedings of Machine Learning Research, Volume 89 von Proceedings of Machine Learning Research, Seite 1574--1583. PMLR, (16--18 Apr 2019)
J. Song, Y. Chen, und Y. Yue. Proceedings of Machine Learning Research, Volume 89 von Proceedings of Machine Learning Research, Seite 3158--3167. PMLR, (16--18 Apr 2019)
G. Dikov, und J. Bayer. Proceedings of Machine Learning Research, Volume 89 von Proceedings of Machine Learning Research, Seite 730--738. PMLR, (16--18 Apr 2019)
K. Yang, Y. Chen, A. Lee, und Y. Yue. Proceedings of Machine Learning Research, Volume 89 von Proceedings of Machine Learning Research, Seite 3410--3419. PMLR, (16--18 Apr 2019)
M. Titsias, und F. Ruiz. Proceedings of Machine Learning Research, Volume 89 von Proceedings of Machine Learning Research, Seite 167--176. PMLR, (16--18 Apr 2019)
A. Grover, und S. Ermon. Proceedings of Machine Learning Research, Volume 89 von Proceedings of Machine Learning Research, Seite 2514--2524. PMLR, (16--18 Apr 2019)
D. Molchanov, V. Kharitonov, A. Sobolev, und D. Vetrov. Proceedings of Machine Learning Research, Volume 89 von Proceedings of Machine Learning Research, Seite 2593--2602. PMLR, (16--18 Apr 2019)
M. Wu, N. Goodman, und S. Ermon. Proceedings of Machine Learning Research, Volume 89 von Proceedings of Machine Learning Research, Seite 2877--2886. PMLR, (16--18 Apr 2019)
F. Nielsen, B. Muzellec, und R. Nock. (2016)cite arxiv:1609.07082Comment: 21 pages, 8 figures, 5 tables, extend ICIP 2016 paper entitled "classification With Mixtures of Curved Mahalanobis Metrics".
G. Marti, S. Andler, F. Nielsen, und P. Donnat. (2016)cite arxiv:1604.08634Comment: Accepted at IEEE Workshop on Statistical Signal Processing (SSP 2016).
F. Nielsen, und R. Nock. (2013)cite arxiv:1309.3029Comment: 11 pages, two tables, no figure. Java(TM) code available online at http://www.informationgeometry.org/fDivergence/.
F. Nielsen. (2013)cite arxiv:1301.3578Comment: To appear in Connected at Infinity II: On the work of Indian mathematicians (R. Bhatia and C.S. Rajan, Eds.), special volume of Texts and Readings In Mathematics (TRIM), Hindustan Book Agency, 2013.
F. Nielsen, und R. Nock. (2011)cite arxiv:1112.4221Comment: 9 pages, 3 figures; Journal of Physics A: Mathematical and Theoretical, December 2011. IOP.
A. Cichocki, R. Zdunek, und S. Amari. Independent Component Analysis and Blind Signal Separation, Seite 32--39. Berlin, Heidelberg, Springer Berlin Heidelberg, (2006)
N. Meinshausen, und P. Bühlmann. (2006)cite arxiv:math/0608017Comment: Published at http://dx.doi.org/10.1214/009053606000000281 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org).
T. Osogami. (2017)cite arxiv:1708.06008Comment: 36 pages. The topics covered in this paper are presented in Part I of IJCAI-17 tutorial on energy-based machine learning. https://researcher.watson.ibm.com/researcher/view_group.php?id=7834.
J. Lucas, G. Tucker, R. Grosse, und M. Norouzi. (2019)cite arxiv:1911.02469Comment: 11 main pages, 10 appendix pages. 13 figures total. Accepted at 33rd Conference on Neural Information Processing Systems (NeurIPS 2019).
C. Maddison, D. Paulin, Y. Teh, und A. Doucet. (2019)cite arxiv:1902.02257Comment: Major revision, including simpler equivalent conditions for dual relative smoothness and applications to exponential penalty functions and p-norm regression.
Y. Wu, G. Wayne, A. Graves, und T. Lillicrap. (2018)cite arxiv:1804.01756Comment: Published as a conference paper at ICLR 2018 (corrected typos in revision).