Abstract
Matrix completion has been rapidly grown interested in areas of engineering and applied science. however, most of applications are aim at single variate matrix. In fact, majority applications datasets express in form of multivariate matrix, developing multivariate matrix application is very necessary. The important is when the missing values too many, matrix completion of take advantage of active learning performance better than standard matrix completion. Although, several combining active learning for matrix completion solutions have been proposed, and most of them based on query strategy. But none of them emphasize the important location of matrix for recovering a matrix. In this paper, we design active multivariate matrix completion. The goal of this algorithm is that find a important location of matrix for matrix completion and combine rank aggregation to select query entries. Experiment evaluation base on images datasets. when we query a small amount of missing entries, the proposed active multivariate matrix completion efficiently raise the accuracy of matrix completion and give the important position of missing entries.
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Liu, T., Wu, Q., Zhang, W., Cao, X. (2018). Active Multivariate Matrix Completion. In: Chen, Q., Wu, J., Zhang, S., Yuan, C., Batten, L., Li, G. (eds) Applications and Techniques in Information Security. ATIS 2018. Communications in Computer and Information Science, vol 950. Springer, Singapore. https://doi.org/10.1007/978-981-13-2907-4_16
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DOI: https://doi.org/10.1007/978-981-13-2907-4_16
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