Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
We present a new approach to managing failures and evolution in large, complex distributed systems using runtime paths. We use the paths that requests follow as e through the syst...
Mike Y. Chen, Anthony Accardi, Emre Kiciman, David...
—In distributed real-time embedded systems (DRE), it is common to model an application as a set of task chains. Each chain is activated cyclically and must complete before an end...
Beyond conventional linear and kernel-based feature extraction, we present a more generalized formulation for feature extraction in this paper. Two representative algorithms using ...
We present randomized constructions of linear-time encodable and decodable codes that can transmit over lossy channels at rates extremely close to capacity. The encoding and decod...
Michael Luby, Michael Mitzenmacher, Mohammad Amin ...