In multi-task learning our goal is to design regression or classification models for each of the tasks and appropriately share information between tasks. A Dirichlet process (DP) ...
Computer experiments often require dense sweeps over input parameters to obtain a qualitative understanding of their response. Such sweeps can be prohibitively expensive, and are ...
Robert B. Gramacy, Herbert K. H. Lee, William G. M...
A single signal processing algorithm can be represented by many mathematically equivalent formulas. However, when these formulas are implemented in code and run on real machines, ...
In distributed stream processing environments, large numbers of continuous queries are distributed onto multiple servers. When one or more of these servers become overloaded due t...
Immersive, interactive applications grouped under the concept of Immersipresence require on-line processing and mixing of multimedia data streams and structures. One critical issu...