مقاله الگوریتم های مقیاس پذیر برای یادگیری چند نمونه

عنوان مقاله فارسی: الگوریتم های مقیاس پذیر برای یادگیری چند نمونه عنوان مقاله لاتین: Scalable Algorithms for Multi-Instance Learning نویسندگان: Xiu-Shen Wei; Jianxin Wu; Zhi-Hua Zhou تعداد صفحات: 12 سال انتشار: 2017 زبان: لاتین Abstract: Multi-instance learning (MIL) has been widely applied to diverse applications involving complicated data objects, such as images and genes. However, most existing MIL algorithms can only handle small- or moderate-sized data. In order to deal with large-scale MIL problems, we propose MIL based on the vector of locally aggregated descriptors representation (miVLAD) and MIL based on the Fisher vector representation (miFV), two efficient and scalable MIL algorithms. They map the original MIL bags into new vector representations using their corresponding