We present a novel approach to statistical shape analysis of anatomical structures based on small sample size learning techniques. The high complexity of shape models used in medic...
Polina Golland, W. Eric L. Grimson, Martha Elizabe...
Commodity operating systems entrusted with securing sensitive data are remarkably large and complex, and consequently, frequently prone to compromise. To address this limitation, ...
Xiaoxin Chen, Tal Garfinkel, E. Christopher Lewis,...
We address the problem of maintaining continuous skyline queries efficiently over dynamic objects with d dimensions. Skyline queries are an important new search capability for mult...
Growth in government investment, academic research, and commercial question answering (QA) systems is motivating a need for increased planning and coordination. The internationali...
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...