Multiple instance learning

Depending on the type and variation in training data, machine learning can be roughly categorized into three frameworks: supervised learning… (More)
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Highly Cited
2015
Highly Cited
2015
The recent development in learning deep representations has demonstrated its wide applications in traditional vision tasks like… (More)
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Highly Cited
2014
Highly Cited
2014
Multiple instance learning (MIL) can reduce the need for costly annotation in tasks such as semantic segmentation by weakening… (More)
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2014
2014
We present a multi-class, multiple instance learning (MIL) algorithm using the dictionary learning framework where the data is… (More)
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2013
2013
We propose a large margin method for asymmetric learning with ellipsoids, called eMIL, suited to multiple instance learning (MIL… (More)
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Highly Cited
2011
Highly Cited
2011
In this paper, we address the problem of tracking an object in a video given its location in the first frame and no other… (More)
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Highly Cited
2011
Highly Cited
2011
Multiple instance learning (MIL) is a paradigm in supervised learning that deals with the classification of collections of… (More)
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2010
2010
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two… (More)
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2010
2010
In this paper, we propose to solve multiple instance learning problems using a dissimilarity representation of the objects. Once… (More)
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Highly Cited
2007
Highly Cited
2007
We present a new approach to multiple instance learning (MIL) that is particularly effective when the positive bags are sparse (i… (More)
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Highly Cited
2005
Highly Cited
2005
We empirically study the relationship between supervised and multiple instance (MI) learning. Algorithms to learn various… (More)
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