Multi-instance multi-label learning (MIML) refers to the
learning problems where each example is represented by a
bag/collection of instances and is labeled by multiple labels.
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Rong Jin (Michigan State University), Shijun Wang...
Error Subspace Statistical Estimation (ESSE), an uncertainty prediction and data assimilation methodology employed for real-time ocean forecasts, is based on a characterization an...
Constantinos Evangelinos, Pierre F. J. Lermusiaux,...
Localization is one of the fundamental problems in mobile robotics. Without knowledge about their position mobile robots cannot e ciently carry out their tasks. In this paper we pr...
Massive data streams are now fundamental to many data processing applications. For example, Internet routers produce large scale diagnostic data streams. Such streams are rarely s...
Graham Cormode, Mayur Datar, Piotr Indyk, S. Muthu...
Groupwise registration has been widely investigated in recent years due to its importance in analyzing population data in many clinical applications. To our best knowledge, most o...