A key challenge in recommender system research is how to effectively profile new users, a problem generally known as cold-start recommendation. Recently the idea of progressivel...
Low-Rank Representation (LRR) [16, 17] is an effective method for exploring the multiple subspace structures of data. Usually, the observed data matrix itself is chosen as the dic...
—Sensor networks are often redundant by design; this is often done in order to achieve reliability in information processing. In many cases, the redundancy relationships between ...
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Disconnection and reconnection are common problems for users of synchronous groupware, but these problems are not easy for developers to handle because of the wide range of scenar...