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Ranking as Learning Structured Outputs

Ranking as Learning Structured Outputs

This video was recorded at NIPS Workshop on Kernel Methods and Structured Domains / NIPS Workshop on Large Scale Kernel Machines, Whistler 2005. Kernel Methods and Structured Domains Substantial recent work in machine learning has focused on the problem of dealing with inputs and outputs on more complex domains than are provided for in the classical regression/classification setting. Structured representations can give a more informative view of input domains, which is crucial for the development of successful learning algorithms: application areas include determining protein structure and protein-protein interaction; part-of-speech tagging; the organization of web documents into hierarchies; and image segmentation. Likewise, a major research direction is in the use of structured output... Show More


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