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Multiple instance learning

Depending on the type and variation in training data, machine learning can be roughly categorized into three frameworks: supervised learning… 
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Papers overview

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2019
2019
Multiple instance learning (MIL) is a weakly supervised learning method where a single label is assigned to a group of instances… 
2018
2018
Object detection and tracking is the basic capability of mobile robots to achieve natural human–robot interaction. In this paper… 
2017
2017
Countless challenges in engineering require the intelligent combining (aka fusion) of data or information from multiple sources… 
2016
2016
In subjective evaluation of dysarthric speech, the inter-rater agreement between clinicians can be low. Disagreement among… 
2012
2012
Multiple Instance Learning (MIL) is concerned with learning from sets (bags) of feature vectors (instances), where the individual… 
2011
2011
This paper proposes a Co-training Multiple Instance Learning algorithm (CoMIL). Our framework is based on the co-training… 
2010
2010
Dimensionality reduction and feature selection in particular are known to be of a great help for making supervised learning more… 
2009
2009
In many machine learning applications, precisely labeled data is either burdensome or impossible to collect. Multiple Instance… 
2009
2009
We propose a new Web image gathering system which employs the region-based bag-of-features representation and multiple instance… 
2007
2007
In this paper, we propose a Semi-Supervised Multiple-Instance Learning (SSMIL) algorithm, and apply it to Localized Content-Based…