Zobrazeno 1 - 10
of 179
pro vyhledávání: '"Patrini, G"'
Autor:
Patrini, G., van den Berg, R., Forré, P., Carioni, M., Bhargav, S., Welling, M., Genewein, T., Nielsen, F., Globerson, A., Silva, R.
Publikováno v:
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence: UAI 2019, Tel Aviv, Israel, July 22-25, 2019
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence
Optimal transport offers an alternative to maximum likelihood for learning generative autoencoding models. We show that minimizing the p-Wasserstein distance between the generator and the true data distribution is equivalent to the unconstrained min-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=narcis______::6cb94aa7b1b24c0e3e420f510cd42a63
https://dare.uva.nl/personal/pure/en/publications/sinkhorn-autoencoders(98128873-a76f-4489-895d-f5092d750e22).html
https://dare.uva.nl/personal/pure/en/publications/sinkhorn-autoencoders(98128873-a76f-4489-895d-f5092d750e22).html
Autor:
Patrini, G., Bhargav, S., Den Berg, R., Welling, M., Forré, P., Genewein, T., Carioni, M., Frank Nielsen
Publikováno v:
Scopus-Elsevier
Optimal transport offers an alternative to maximum likelihood for learning generative autoencoding models. We show that minimizing the p-Wasserstein distance between the generator and the true data distribution is equivalent to the unconstrained min-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3276570472b904cf0c52eaf872c6e14e
Publikováno v:
Scopus-Elsevier
Computing a Nash equilibrium (NE) is a central task in computer science. An NE is a particularly appropriate solution concept for two-agent settings because coalitional deviations are not an issue. However, even in this case, finding an NE is PPAD-co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c65fbddaf264249b1742bc79ce0edb1b