Interactive learning using a "society of models"

Interactive learning using a "society of models"

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by T. P. Minka , R. W. Picard

Venue:	SUBMITTED TO SPECIAL ISSUE OF PATTERN RECOGNITION ON IMAGE DATABASE: CLASSIFICATION AND RETRIEVAL
Citations:	132 - 10 self

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@MISC{Minka_interactivelearning,
    author = {T. P. Minka and R. W. Picard},
    title = { Interactive learning using a "society of models"},
    year = {}
}

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Abstract

Digital library access is driven by features, but features are often context-dependent and noisy, and their relevance for a query is not always obvious. This paper describes an approach for utilizing many data-dependent, user-dependent, and task-dependent features in a semi-automated tool. Instead of requiring universal similarity measures or manual selection of relevant features, the approach provides a learning algorithm for selecting and combining groupings of the data, where groupings can be induced by highlyspecialized and context-dependent features. The selection process is guided by arichexample-based interaction with the user. The inherent combinatorics

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