Local similarity learning for pairwise constraint propagation
نویسندگان
چکیده
منابع مشابه
Pairwise Constraint Propagation: A Survey
As one of the most important types of (weaker) supervised information in machine learning and pattern recognition, pairwise constraint, which specifies whether a pair of data points occur together, has recently received significant attention, especially the problem of pairwise constraint propagation. At least two reasons account for this trend: the first is that compared to the data label, pair...
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Overview Different vectorial and / or (dis)similarity representations can be produced for a given data. These distinct representations or data generating models have typically been used individually, in single classifiers or single clustering algorithms, or simultaneously, as in classifier combination techniques or cluster ensemble methods, depending, respectively, on whether working under a su...
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This paper presents a graph-based learning approach to pairwise constraint propagation on multi-view data. Although pairwise constraint propagation has been studied extensively, pairwise constraints are usually defined over pairs of data points from a single view, i.e., only intra-view constraint propagation is considered for multi-view tasks. In fact, very little attention has been paid to int...
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Our aim in this paper is to maintain the global consistency of a constraint satisfaction problem involving temporal constraints anytime a new constraint is added. This problem is of practical relevance since it is often required to check whether a solution to a CSP continues to be a solution when a new constraint is added and if not, whether a new solution satisfying the old and new constraints...
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Multiple-Instance Learning (MIL) has attracted much attention of the machine learning community in recent years and many real-world applications have been successfully formulated as MIL problems. Over the past few years, several Instance Selection-based MIL (ISMIL) algorithms have been presented by using the concept of the embedding space. Although they delivered very promising performance, the...
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ژورنال
عنوان ژورنال: Multimedia Tools and Applications
سال: 2014
ISSN: 1380-7501,1573-7721
DOI: 10.1007/s11042-013-1796-y