Fast Multi-Instance Multi-Label Learning

@article{Huang2014FastMM,
  title={Fast Multi-Instance Multi-Label Learning},
  author={Sheng-Jun Huang and Zhi-Hua Zhou},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  year={2014}
}
In many real-world tasks, particularly those involving data objects with complicated semantics such as images and texts, one object can be represented by multiple instances and simultaneously be associated with multiple labels. Such tasks can be formulated as multi-instance multi-label learning (MIML) problems, and have been extensively studied during the past few years. Existing MIML approaches have been found useful in many applications; however, most of them can only handle moderate-sized… CONTINUE READING
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