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 has attracted an increasing attention from many domains, because of its great potential applications. Although many learning methods have been witnessed, two major challenges are still not handled very well. They are the correlations and the high dimensionality of data. In this paper, we exploit the inherent property of the multi-label data and propose an effective sparse multi-label...
Multi-label classification allows an instance to be associated with multiple labels. Compared with other classification tasks, multi-label classification also suffers from the problem of high data dimension. However, the existing dimensionality reduction (DR) methods are not very appropriate for multi-label data. In this paper, we proposed a supervised DR method, named the compressed partial least...
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.