Masaya Murata

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Information needs expressed by using the same query for a search engine might be totally different, whether on week days or weekends, or during the day or at night. For queries having no temporal changes in search intentions, the same search results ranking may be returned regardless of the time, but for those with temporal changes the ranking must be(More)
— A Kalman filter (KF) is state-of-the-art for estimating states of linear-Gaussian state-space models. The KF selects an expectation of a posterior probability density function of state and the expectation is an analytic solution for minimizing the square estimation error. The estimate of KF is therefore optimal, however, simultaneously inherits the(More)
Users of text retrieval systems input only a few keywords or sometimes just one keyword to the systems even if they had complex information needs. Due to the lack of query keywords, it becomes hard to return relevant search results that satisfy the demands of each user. Because digital documents, in contrast to queries, are generally composed of many kinds(More)
— Kalman filter (KF) design is well established for perfectly known linear system and observation models. Real-world phenomena, however, have significant associated uncertainties , and the tuning of the KF is not so straightforward for tackling them. In this paper, we present a method of designing a robust filter for nonlinear systems with model parameter(More)