Multi-Kernel Gaussian Processes
نویسندگان
چکیده
Although Gaussian process inference is usually formulated for a single output, in many machine learning problems the objective is to infer multiple tasks jointly, possibly exploring the dependencies between them to improve results. Real world examples of this problem include ore mining where the objective is to infer the concentration of several chemical components to assess the ore quality. Similarly, in robotics and control problems there are more than one actuator and the understanding and accurate modeling of the dependencies between the control outputs can significantly improve the controller.
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تاریخ انتشار 2011