This paper presents an approach for computing global distance metrics that minimize the k-NN leave-one-out (LOO) error. The approach optimizes an energy ...
This paper presents an approach for computing global distance metrics that minimize the k-NN leave- one-out (LOO) error. The approach optimizes an en-.
This paper presents an approach for computing global distance metrics that minimize the k-NN leave-one-out (LOO) error. The approach optimizes an energy ...
Evaluation of the proposed approach for computing global distance metrics that minimize the k-NN leave-one-out (LOO) error showed that it was able to ...
This paper presents an approach for computing global distance metrics that minimize the k-NN leave-one-out (LOO) error. The approach optimizes an energy ...
This paper presents an approach for computing global distance metrics that minimize the k-NN leave-one-out (LOO) error. The approach optimizes an energy ...
Metric learning by directly minimizing the k-NN training error. Conference paper (2012). Authors. V.C. Dinh Pattern Recognition and Bioinformatics - EEMCS.
Chernoff, K, Loog, M & Nielsen, M 2012, Metric learning by directly minimizing the k-NN training error. in 2012 21st International Conference on Pattern ...
Dinh, VC., Loog, M., & Nielsen, M. (2012). Metric learning by directly minimizing the k-NN training error. In SN (Ed.), Proceedings of 21st International ...
RIS. Chernoff, K., Loog, M., & Nielsen, M. (2012). Metric learning by directly minimizing the k-NN training error. In 2012 21st International Conference on ...