The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Multi-label learning deals with the problem where each instance may be associated with multiple labels simultaneously, and how to discover and exploit the label correlations is one of important research issues. In this paper, we propose a novel sparse and low-rank representation-based method for multi-label classification (SLMLC), which can automatically exploit the asymmetric correlations among labels...
The selection of multi-view features plays an important role for classifying multi-view data, especially the data with high dimension. In this paper, a novel multi-view feature selection method via joint local pattern-discrimination and global label-relevance analysis (mPadal) is proposed. Different from the previous methods which globally select the multi-view features directly via view-level analysis,...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.