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.
Transfer learning targets to leverage knowledge from one domain for tasks in a new domain. It finds abundant applications, such as text/sentiment classification. Many previous works are based on cluster analysis, which assume some common clusters shared by both domains. They mainly focus on the one-to-one cluster correspondence to bridge different domains. However, such a correspondence scheme might...
Kernel-based clustering is one of the most popular methods for partitioning nonlinearly separable dataset. However, exhaustive search for the global optimum is NP-hard. Iterative procedure such as k-means can be used to seek one of the local minima. Unfortunately, it is easily trapped into degenerate local minima when the prototypes of clusters are ill-initialized. In this paper, we restate the optimization...
The purpose of this paper is to propose new clustering technique on manifolds. This is achieved mainly with the help of tangent spaces that are determined by manifold learning. We embed a new searching algorithm based on differential evolution (DE). We present a simple convergence analysis with a design of experimental framework.
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.