5. The method of claim 4 , wherein the retrieving the plurality of images from the searching of the input image dataset that each comprise at least one of the query subset plurality of attributes further comprises: predicting the retrieved plurality of images by maximizing weighted feature vectors extracted by each of the trained image attribute detectors as a function of a component modeling an appearance of the attribute of the each of the trained image attribute detectors, and a component modeling a dependency between the attribute of the each of the attributes of the trained image attribute detectors to another one of the annotated attributes in the training dataset of images that is not in the query subset plurality of attributes.
5. The method of claim 4 , wherein the retrieving the plurality of images from the searching of the input image dataset that each comprise at least one of the query subset plurality of attributes further comprises: predicting the retrieved plurality of images by maximizing weighted feature vectors extracted by each of the trained image attribute detectors as a function of a component modeling an appearance of the attribute of the each of the trained image attribute detectors, and a component modeling a dependency between the attribute of the each of the attributes of the trained image attribute detectors to another one of the annotated attributes in the training dataset of images that is not in the query subset plurality of attributes. 6. The method of claim 5 , wherein the learning the pair-wise correlations is a max-margin training.