Correlation mining has gained great success in many application domains for its ability to capture the underlying dependency between objects. However, the research of correlation ...
This paper introduces a class of conditional inclusion dependencies (CINDs), which extends traditional inclusion dependencies (INDs) by enforcing bindings of semantically related ...
We address the problem of instruction selection for Multi-Output Instructions (MOIs), producing more than one result. Such inherently parallel hardware instructions are very commo...
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
ABSTRACT. Estimating a non-uniformly sampled function from a set of learning points is a classical regression problem. Kernel methods have been widely used in this context, but eve...