We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise, a problem closely related to several cryptograph...
In many image retrieval applications, the mapping between highlevel semantic concept and low-level features is obtained through a learning process. Traditional approaches often as...
In this work we consider ontologies as knowledge structures that specify terms, their properties and relations among them to enable knowledge extraction from texts. We represent o...
Learning temporal graph structures from time series data reveals important dependency relationships between current observations and histories. Most previous work focuses on learn...
Traditional Web-based educational systems still have several shortcomings when comparing with a real-life classroom teaching, such as lack of contextual and adaptive support, lack...