Data-driven metric adaptation is proposed for proteome analysis of 2D-gel electrophoretic plots aiming at identification of stress related proteins in two barley cultivars with different response towards different salt stress conditions. Gradient descent is applied to the ratio of intraand inter-class distance sums to optimize the matrix parameters of generalized Mahalanobis distances in order ...

We propose an unsupervised “local learning” algorithm for learning a metric in the input space. Geometrically, for a given query point, the algorithm finds the minimum volume ellipsoid (MVE) covering its neighborhood which characterizes the correlations and variances of its neighborhood variables. Algebraically, the algorithm maximizes the determinant of the local covariance matrix which amount...