Labeled data for classification could often be obtained by sampling that restricts or favors choice of certain classes. A classifier trained using such data will be biased, resulti...
Specific requirements of stream processing on the Grid are discussed. We argue that when the stream processing paradigm is used for cluster computing, the processing components c...
We introduce tiered clustering, a mixture model capable of accounting for varying degrees of shared (context-independent) feature structure, and demonstrate its applicability to i...
Randomized protocols for hiding private information can be regarded as noisy channels in the information-theoretic sense, and the inference of the concealed information can be reg...
an be used to abstract away from the physical reality by describing it as components that exist in discrete states with probabilistically invoked actions that change the state. The...
Duncan Gillies, David Thornley, Chatschik Bisdikia...