Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Määttä, Jussi"'
Autor:
Määttä, Jussi, Bazaliy, Viacheslav, Kimari, Jyri, Djurabekova, Flyura, Nordlund, Kai, Roos, Teemu
Publikováno v:
Neural Networks 133, 123 (2021)
Many applications, especially in physics and other sciences, call for easily interpretable and robust machine learning techniques. We propose a fully gradient-based technique for training radial basis function networks with an efficient and scalable
Externí odkaz:
http://arxiv.org/abs/2004.02569
Autor:
Määttä, Jussi, Bazaliy, Viacheslav, Kimari, Jyri, Djurabekova, Flyura, Nordlund, Kai, Roos, Teemu
Publikováno v:
In Neural Networks January 2021 133:123-131
The technique of Schroeppel and Shamir (SICOMP, 1981) has long been the most efficient way to trade space against time for the SUBSET SUM problem. In the random-instance setting, however, improved tradeoffs exist. In particular, the recently discover
Externí odkaz:
http://arxiv.org/abs/1303.0609
Subset Selection in Linear Regression using Sequentially Normalized Least Squares: Asymptotic Theory
Publikováno v:
Scandinavian Journal of Statistics, 2016 Jun 01. 43(2), 382-395.
Externí odkaz:
http://www.jstor.org/stable/24887002
Autor:
Määttä, Jussi1 jussi.maatta@helsinki.fi, Roos, Teemu1
Publikováno v:
PLoS ONE. 4/1/2016, Vol. 11 Issue 4, p1-21. 21p.