We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
A central question in designing server farms today is how to efficiently provision the number of servers to extract the best performance under unpredictable demand patterns while ...
Anshul Gandhi, Varun Gupta, Mor Harchol-Balter, Mi...
We present a motion classification approach to detect movements of interest (abnormal motion) based on local feature modeling within spatio-temporal detectors. The modeling is pe...
The relationship between project selection and requirements analysis is important, yet has not received much attention. The decisions made during project selection directly affect...
One of the inherent problems in pattern recognition is the undersampled data problem, also known as the curse of dimensionality reduction. In this paper a new algorithm called pai...