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Avtomatika i Telemekhanika, 2015, Issue 5, Pages 100–120
(Mi at14235)
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This article is cited in 3 scientific papers (total in 3 papers)
Topical issue
On sequential hypotheses testing via convex optimization
A. B. Juditskya, A. S. Nemirovskib a LJK, Universite Grenoble Alpes, Grenoble, France
b Georgia Institute of Technology, Atlanta, USA
Abstract:
We propose a new approach to sequential testing which is an adaptive (on-line) extension of the (off-line) framework developed in [1]. It relies upon testing of pairs of hypotheses in the case where each hypothesis states that the vector of parameters underlying the distribution of observations belongs to a convex set. The nearly optimal under appropriate conditions test is yielded by a solution to an efficiently solvable convex optimization problem. The proposed methodology can be seen as a computationally friendly reformulation of the classical sequential testing.
Citation:
A. B. Juditsky, A. S. Nemirovski, “On sequential hypotheses testing via convex optimization”, Avtomat. i Telemekh., 2015, no. 5, 100–120; Autom. Remote Control, 76:5 (2015), 809–825
Linking options:
https://www.mathnet.ru/eng/at14235 https://www.mathnet.ru/eng/at/y2015/i5/p100
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Statistics & downloads: |
Abstract page: | 279 | Full-text PDF : | 59 | References: | 35 | First page: | 26 |
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