多示例学习问题研究进展综述

A review of multi-instance learning research

多示例学习是一种特殊的机器学习问题,近年来得到了广泛的关注和研究,许多不同类型的多示例学习算法被提出,用以处理各个领域中的实际问题.针对多示例学习的算法研究和应用进行了较为详细的综述,介绍了多示例学习的各种背景假设,从基于示例水平、包水平、嵌入空间三个方面对多示例学习的常见算法进行了描述,并给出了多示例学习的算法拓展和若干领域的主要应用.

Multi-instance learning is a special kind of machine learning problem, has received extensive attention and been researched on in recent years. Many different types of multi-instance learning algorithms have been proposed to deal with practical problems in various fields. This paper reviews the algorithm research and application of multiinstance learning in detail, introduces various background assumptions,and introduces multi-instance learning from three aspects： instance level, bag level, and embedded space.Finally we provide the algorithm extensions and maior applications in several areas.