Currently, a large amount of data can be best represented as graphs, e.g., social networks, protein interaction networks, etc. The analysis of these networks is an urgent research ...
How do connected components evolve? What are the regularities that govern the dynamic growth process and the static snapshot of the connected components? In this work, we study pat...
U. Kang, Mary McGlohon, Leman Akoglu, Christos Fal...
Many real world applications such as sensor networks and other monitoring applications naturally generate probabilistic streams that are highly correlated in both time and space. ...
Much recent research has been devoted to learning algorithms for deep architectures such as Deep Belief Networks and stacks of auto-encoder variants, with impressive results obtai...
Dumitru Erhan, Yoshua Bengio, Aaron C. Courville, ...
Matrix factorization is a successful technique for building collaborative filtering systems. While it works well on a large range of problems, it is also known for requiring signi...
Alexandros Karatzoglou, Alexander J. Smola, Markus...