Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Müller, Kilian"'
Autor:
Hesslow, Daniel, Cappelli, Alessandro, Carron, Igor, Daudet, Laurent, Lafargue, Raphaël, Müller, Kilian, Ohana, Ruben, Pariente, Gustave, Poli, Iacopo
Randomized Numerical Linear Algebra (RandNLA) is a powerful class of methods, widely used in High Performance Computing (HPC). RandNLA provides approximate solutions to linear algebra functions applied to large signals, at reduced computational costs
Externí odkaz:
http://arxiv.org/abs/2104.14429
Autor:
Launay, Julien, Poli, Iacopo, Müller, Kilian, Pariente, Gustave, Carron, Igor, Daudet, Laurent, Krzakala, Florent, Gigan, Sylvain
The scaling hypothesis motivates the expansion of models past trillions of parameters as a path towards better performance. Recent significant developments, such as GPT-3, have been driven by this conjecture. However, as models scale-up, training the
Externí odkaz:
http://arxiv.org/abs/2012.06373
Autor:
Launay, Julien, Poli, Iacopo, Müller, Kilian, Carron, Igor, Daudet, Laurent, Krzakala, Florent, Gigan, Sylvain
As neural networks grow larger and more complex and data-hungry, training costs are skyrocketing. Especially when lifelong learning is necessary, such as in recommender systems or self-driving cars, this might soon become unsustainable. In this study
Externí odkaz:
http://arxiv.org/abs/2006.01475