We initiate a new distance metric learning technique recognized as ambiguously supervised structural metric learning to find out discriminative Mahalanobis distance metric that is based on weak supervision data. For improving the performance, two affinity matrices are combined to get a fused affinity matrix which is used for face naming. When specified a collection of images, in which each of the image contains numerous faces and is linked by few names in corresponding caption, the purpose of...
Topics: Images, Regularized low-rank, Affinity matrices, Face naming, Mahalanobis distance metric, Computer...
Constrained Clustering Advances In Algorithms, Theory, And Applications
Topics: clustering, data, constraints, cluster, pairwise, algorithm, constrained, clusters, learning,...
From the bitsavers.org collection, a scanned-in computer-related document. mit :: ai :: aim :: AIM-1521
Topics: face, distance, pattern, patterns, vector, image, canonical, detection, gaussian, metric, canonical...
