首页>
外国专利>
MASSIVE CLUSTERING OF DISCRETE DISTRIBUTIONS
MASSIVE CLUSTERING OF DISCRETE DISTRIBUTIONS
展开▼
机译:离散分布的大规模聚类
展开▼
页面导航
摘要
著录项
相似文献
摘要
The trend of analyzing big data in artificial intelligence requires more scalable machine learning algorithms, among which clustering is a fundamental and arguably the most widely applied method. To extend the applications of regular vector-based clustering algorithms, the Discrete Distribution (D2) clustering algorithm has been developed for clustering bags of weighted vectors which are well adopted in many emerging machine learning applications. The high computational complexity of D2-clustering limits its impact in solving massive learning problems. Here we present a parallel D2-clustering algorithm with substantially improved scalability. We develop a hierarchical structure for parallel computing in order to achieve a balance between the individual-node computation and the integration process of the algorithm. The parallel algorithm achieves significant speed-up with minor accuracy loss.
展开▼