Graph embedding learns low-dimensional representations for nodes or edges on the graph, which is widely applied in many real-world applications. Excessive graph mining promotes research of attack methods embedding. Most generate perturbations that maximize deviation prediction confidence. They are difficult to accurately misclassify instances into target label, and nonminimized more easily dete...

The radioautographic distribution of the label of galactose-H(3) was compared with that of glucose-H(3) in a series of secretory cells of the rat. Whereas the glucose label appeared in all mucous cells, the galactose label was incorporated only into certain mucous cells. Whenever either label was incorporated, however, it was located first in the Golgi region and later in the secretion product,...

Using a monoclonal antibody to chondroitin 6-sulfate, a major constituent of the cone matrix sheath, the location of the cone matrix sheath and the relative distribution of interphotoreceptor retinoid-binding protein (IRBP) was examined by light and electron microscopic immunocytochemistry. Chondroitin 6-sulfate immunoreactivity was localized to regions surrounding cone outer and inner segments...

The half-lives of proteins of mitochondria and a well characterized set of mitochondrial subfractions have been estimated using two methods based on incorporation of a minimally reutilized amino acid precursor, [‘‘Clbicarbonate. The apparent average rate constants of protein degradation were measured on rat liver homogenate, mitochondria, and distinct outer compartment, inner membrane, and matr...

The knowledge graph is an effective tool for improving natural language processing, but manually annotating enormous amounts of expensive. Academics have conducted research on entity and relation extraction techniques, among which, the end-to-end table-filling approach a popular direction achieving joint extraction. However, once table has been populated in uniform label space, large number nul...

Multi-label image classification is of significant interest due to its major role in real-world web image analysis applications such as large-scale image retrieval and browsing. Recently, matrix completion (MC) has been developed to deal with multi-label classification tasks. MC has distinct advantages, such as robustness to missing entries in the feature and label spaces and a natural ability ...

The label propagation has the benefits of nearly-linear running time and easy implementation. In this paper, we make use of the label propagation to propose a new weight measure, and present a supervised locality projection analysis (SLPA) method for plant leaf classification. Firstly, we apply Warshall algorithm to label propagation and get the label matrix, then incorporate it into the weight...

In many multi-label learning problems, especially as the number of labels grow, it is challenging to gather completely annotated data. This work presents a new approach for multi-label learning from incomplete annotations. The main assumption is that because of label correlation, the true label matrix as well as the soft predictions of classifiers shall be approximately low rank. We introduce a...