Learning Nonlinearly Parametrized Decision Regions
نویسندگان
چکیده
منابع مشابه
Learning Nonlinearly Parametrized Decision Regions
In this paper we present a deterministic analysis of an online scheme for learning very general classes of nonlinearly parametrized decision regions. The only input required is a sequence ((xk; yk))k2Z+ of data samples, where yk = 1 if xk belongs to the decision region of interest, and yk = 1 otherwise. Averaging results and Lyapunov theory are used to prove the stability of the scheme. In the ...
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In this paper we present a deterministic analysis of an online scheme for learning very general classes of nonlinearly parametrized decision regions. The only input required is a sequence ((x k ; y k)) k2Z + of data samples, where y k = 1 if x k belongs to the decision region of interest, and y k = ?1 otherwise. Averaging results and Lyapunov theory are used to prove the stability of the scheme...
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ژورنال
عنوان ژورنال: IFAC Proceedings Volumes
سال: 1993
ISSN: 1474-6670
DOI: 10.1016/s1474-6670(17)48286-3