In Sparse Coding (SC), input vectors are reconstructed using a sparse linear combination of basis vectors. SC has become a popular method for extracting features from data. For a ...
—We propose an efficient and robust solution for image set classification. A joint representation of an image set is proposed which includes the image samples of the set and thei...
Dierence Bound Matrices (DBMs) are the most commonly used data structure for model checking timed automata. Since long they are being used in successful tools like Kronos or UPPAA...
Querying and integrating sources of structured data from the Web in most cases requires similarity-based concepts to deal with data level conflicts. This is due to the often errone...
Belief Propagation (BP) can be very useful and efficient for performing approximate inference on graphs. But when the graph is very highly connected with strong conflicting intera...