We apply statistical relational learning to a database of criminal and terrorist activity to predict attributes and event outcomes. The database stems from a collection of news ar...
B. Delaney, Andrew S. Fast, W. M. Campbell, C. J. ...
Lack of labeled training examples is a common problem for many applications. In the same time, there is usually an abundance of labeled data from related tasks. But they have diff...
Xiaoxiao Shi, Qi Liu, Wei Fan, Qiang Yang, Philip ...
Most of recommender systems try to find items that are most relevant to the older choices of a given user. Here we focus on the "surprise me" query: A user may be bored ...
We describe a recommender system in the domain of grocery shopping. While recommender systems have been widely studied, this is mostly in relation to leisure products (e.g. movies...
Ming Li, M. Benjamin Dias, Ian H. Jarman, Wael El-...
When labeled examples are limited and difficult to obtain, transfer learning employs knowledge from a source domain to improve learning accuracy in the target domain. However, the...
ErHeng Zhong, Wei Fan, Jing Peng, Kun Zhang, Jiang...