Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
Many sorts of structured data are commonly stored in a multi-relational format of interrelated tables. Under this relational model, exploratory data analysis can be done by using ...
Markus Ojala, Gemma C. Garriga, Aristides Gionis, ...
Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
—With the rapid development of various optical, infrared, and radar sensors and GPS techniques, there are a huge amount of multidimensional uncertain data collected and accumulat...
Motivated by structural properties of the Web graph that support efficient data structures for in memory adjacency queries, we study the extent to which a large network can be com...
Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, ...