This paper addresses the important tradeoff between privacy and learnability, when designing algorithms for learning from private databases. We focus on privacy-preserving logisti...
Ranking is at the heart of many information retrieval applications. Unlike standard regression or classification in which we predict outputs independently, in ranking we are inter...
We consider the problem of transforming a signal to a representation in which the components are statistically independent. When the signal is generated as a linear transformation...
In many data-centric applications it is desirable to use OWL as an expressive schema language where one expresses constraints that need to be satisfied by the (instance) data. Howe...
With a rich variety of forms and types, digital resources are complex data objects. They grows fast in volume on the Web, but hard to be classified efficiently. The paper presents ...