Kota Kawaratani

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In our previous work, we have developed the backward feature selection method based on class regions approximated by ellipsoids. In this paper, we accelerate feature selection by the forward selection search, the symmetric Cholesky factorization, and deletion of duplicated calculations between consecutive factorizations. The feature selection for two data(More)
This paper addresses a problem to decide the combination of risk-reducing plans quickly. The combinatorial problem is formulated as one of the 0–1 integer programming and Branch and Bound is applied. On Branch and Bound, Simplex method for deciding a branching variable and the lower bound, which takes much time. Therefore, we propose the high-speed(More)
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