Zobrazeno 1 - 10
of 254
pro vyhledávání: '"Alex Lamb"'
Autor:
Alex Lamb, Arno Solin, Juho Kannala, Vikas Verma, David Lopez-Paz, Kenji Kawaguchi, Yoshua Bengio
Publikováno v:
Neural Networks. 145:90-106
We introduce Interpolation Consistency Training (ICT), a simple and computation efficient algorithm for training Deep Neural Networks in the semi-supervised learning paradigm. ICT encourages the prediction at an interpolation of unlabeled points to b
Publikováno v:
AAPG Bulletin. 104:357-386
The Mississippian Meramecian play in the greater STACK (Sooner trend Anadarko Basin, Canadian and Kingfisher Counties) play region is an unconventional reservoir in the Anadarko Basin in west central Oklahoma. The play is a fine-grained system compos
Publikováno v:
SN Computer Science. 1
Kuzushiji, a cursive writing style, had been used in Japan for over a thousand years starting from the eighth century. Over 3 million books on a diverse array of topics, such as literature, science, mathematics and even cooking are preserved. However
Publikováno v:
ICDAR
Kuzushiji, a cursive writing style, had been used in Japan for over a thousand years starting from the 8th century. Over 3 millions books on a diverse array of topics, such as literature, science, mathematics and even cooking are preserved. However,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::01b9f1edbccdf28d09c331b8b232a1ae
http://arxiv.org/abs/1910.09433
http://arxiv.org/abs/1910.09433
Publikováno v:
IJCAI
We introduce Interpolation Consistency Training (ICT), a simple and computation efficient algorithm for training Deep Neural Networks in the semi-supervised learning paradigm. ICT encourages the prediction at an interpolation of unlabeled points to b
Autor:
Alex Lamb, Vikas Verma, Kenji Kawaguchi, Alexander Matyasko, Savya Khosla, Juho Kannala, Yoshua Bengio
Adversarial robustness has become a central goal in deep learning, both in the theory and the practice. However, successful methods to improve the adversarial robustness (such as adversarial training) greatly hurt generalization performance on the un
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b3fb95ed0b01c070e4243f33d92fe90c
http://arxiv.org/abs/1906.06784
http://arxiv.org/abs/1906.06784
Publikováno v:
WACV
Deep networks have achieved excellent results in perceptual tasks, yet their ability to generalize to variations not seen during training has come under increasing scrutiny. In this work we focus on their ability to have invariance towards the presen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::776212c0c1891536a3b96891720f3974
Publikováno v:
AISec@CCS
Adversarial robustness has become a central goal in deep learning, both in theory and in practice. However, successful methods to improve the adversarial robustness (such as adversarial training) greatly hurt generalization performance on the unpertu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c232cb6016b70e6f482a39d20fe60004
https://aaltodoc.aalto.fi/handle/123456789/42494
https://aaltodoc.aalto.fi/handle/123456789/42494
Publikováno v:
Proceedings of the 5th Unconventional Resources Technology Conference.
Publikováno v:
Proceedings of the 5th Unconventional Resources Technology Conference.