FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2903397918> ?p ?o ?g. }

• W2903397918 endingPage "304" @default.
• W2903397918 startingPage "281" @default.
• W2903397918 abstract "Estimation of functions from sparse and noisy data is a central theme in machine learning. In the last few years, many algorithms have been developed that exploit Tikhonov regularization theory and reproducing kernel Hilbert spaces. These are the so-called kernel-based methods, which include powerful approaches like regularization networks, support vector machines, and Gaussian regression. Recently, these techniques have also gained popularity in the system identification community. In both linear and nonlinear settings, kernels that incorporate information on dynamic systems, such as the smoothness and stability of the input–output map, can challenge consolidated approaches based on parametric model structures. In the classical parametric setting, the complexity of the model (the model order) needs to be chosen, typically from a finite family of alternatives, by trading bias and variance. This (discrete) model order selection step may be critical, especially when the true model does not belong to the model class. In regularization-based approaches, model complexity is controlled by tuning (continuous) regularization parameters, making the model selection step more robust. In this article, we review these new kernel-based system identification approaches and discuss extensions based on nuclear and [Formula: see text] norms." @default.
• W2903397918 created "2018-12-11" @default.
• W2903397918 creator A5060156794 @default.
• W2903397918 creator A5062648585 @default.
• W2903397918 date "2019-05-03" @default.
• W2903397918 modified "2023-10-03" @default.
• W2903397918 title "System Identification: A Machine Learning Perspective" @default.
• W2903397918 cites W1480376833 @default.
• W2903397918 cites W1496317909 @default.
• W2903397918 cites W1501586228 @default.
• W2903397918 cites W1514443597 @default.
• W2903397918 cites W1515224403 @default.
• W2903397918 cites W1547628305 @default.
• W2903397918 cites W1652432954 @default.
• W2903397918 cites W1862263964 @default.
• W2903397918 cites W1878468619 @default.
• W2903397918 cites W1966096622 @default.
• W2903397918 cites W1968128579 @default.
• W2903397918 cites W1970781863 @default.
• W2903397918 cites W1976310086 @default.
• W2903397918 cites W1976446368 @default.
• W2903397918 cites W1979859909 @default.
• W2903397918 cites W1980759970 @default.
• W2903397918 cites W1981110740 @default.
• W2903397918 cites W1981132042 @default.
• W2903397918 cites W1986280275 @default.
• W2903397918 cites W1990381576 @default.
• W2903397918 cites W1992666150 @default.
• W2903397918 cites W1996538752 @default.
• W2903397918 cites W1999181247 @default.
• W2903397918 cites W1999974018 @default.
• W2903397918 cites W2002355073 @default.
• W2903397918 cites W2006103870 @default.
• W2903397918 cites W2016180374 @default.
• W2903397918 cites W2017332415 @default.
• W2903397918 cites W2017753243 @default.
• W2903397918 cites W2020925091 @default.
• W2903397918 cites W2021065610 @default.
• W2903397918 cites W2024029382 @default.
• W2903397918 cites W2025130480 @default.
• W2903397918 cites W2031879798 @default.
• W2903397918 cites W2032326935 @default.
• W2903397918 cites W2037479549 @default.
• W2903397918 cites W2042107404 @default.
• W2903397918 cites W2047278710 @default.
• W2903397918 cites W2050297026 @default.
• W2903397918 cites W2050810194 @default.
• W2903397918 cites W2054444429 @default.
• W2903397918 cites W2054800525 @default.
• W2903397918 cites W2056145308 @default.
• W2903397918 cites W2058030217 @default.
• W2903397918 cites W2059173978 @default.
• W2903397918 cites W2059283452 @default.
• W2903397918 cites W2062560607 @default.
• W2903397918 cites W2063978378 @default.
• W2903397918 cites W2073892433 @default.
• W2903397918 cites W2074471762 @default.
• W2903397918 cites W2078127574 @default.
• W2903397918 cites W2082233060 @default.
• W2903397918 cites W2083095049 @default.
• W2903397918 cites W2085560853 @default.
• W2903397918 cites W2089899295 @default.
• W2903397918 cites W2092766760 @default.
• W2903397918 cites W2103452139 @default.
• W2903397918 cites W2110652811 @default.
• W2903397918 cites W2113295362 @default.
• W2903397918 cites W2119462269 @default.
• W2903397918 cites W2120115609 @default.
• W2903397918 cites W2121507443 @default.
• W2903397918 cites W2124540387 @default.
• W2903397918 cites W2132320458 @default.
• W2903397918 cites W2134288234 @default.
• W2903397918 cites W2137645797 @default.
• W2903397918 cites W2138019504 @default.
• W2903397918 cites W2142635246 @default.
• W2903397918 cites W2143956139 @default.
• W2903397918 cites W2159425692 @default.
• W2903397918 cites W2159660986 @default.
• W2903397918 cites W2161083632 @default.
• W2903397918 cites W2161765392 @default.
• W2903397918 cites W2162341153 @default.
• W2903397918 cites W2164343167 @default.
• W2903397918 cites W2165867509 @default.
• W2903397918 cites W2168175751 @default.
• W2903397918 cites W2171853113 @default.
• W2903397918 cites W2339048773 @default.
• W2903397918 cites W2595675930 @default.
• W2903397918 cites W2795018701 @default.
• W2903397918 cites W2897282859 @default.
• W2903397918 cites W2911546748 @default.
• W2903397918 cites W2919115771 @default.
• W2903397918 cites W2962875092 @default.
• W2903397918 cites W2962898620 @default.
• W2903397918 cites W2963212984 @default.
• W2903397918 cites W2963974141 @default.
• W2903397918 cites W2964282423 @default.
• W2903397918 cites W3000332379 @default.
• W2903397918 cites W3104887532 @default.

• next