We address the inference control problem in data cubes with some data known to users through external knowledge. The goal of inference controls is to prevent exact values of sensi...
Dyadic data matrices, such as co-occurrence matrix, rating matrix, and proximity matrix, arise frequently in various important applications. A fundamental problem in dyadic data a...
In this paper, we address the problem of learning when some cases are fully labeled while other cases are only partially labeled, in the form of partial labels. Partial labels are...
Data stream values are often associated with multiple aspects. For example, each value from environmental sensors may have an associated type (e.g., temperature, humidity, etc) as...
Tools and techniques used for automatic and smart analysis of huge data repositories of industries, governments, corporations and scientific institutes are the subjects dealt by th...