A new parallel expectation-maximization (EM) algorithm is proposed for large databases. The purpose of the algorithm is to accelerate the operation of the EM algorithm. As a well-known algorithm for estimation in generic statistical problems, the EM algorithm has been widely used in many domains. But it often requires significant computational resources. So it is needed to develop more elaborate methods to adapt the databases to a large number of records or large dimensionality. The parallel EM algorithm is based on partial E-steps which has the standard convergence guarantee of EM. The algorithm utilizes fully the advantage of parallel computation. It was confirmed that the algorithm obtains about 2.6 speedups in contrast with the standard EM algorithm through its application to large databases. The running time will decrease near linearly when the number of processors increasing.
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机译:Comments on, Xuan Li, Shanghong Zhao, Zihang Zhu, Bing Gong, Xingchun Chu, Yongjun Li, Jing Zhao and Yun Liu 'an optical millimeter-wave generation scheme based on two parallel dual-parallel Mach-Zehnder modulators and polarization multiplexing', Journal of Modern Optics, 2015
机译:LTE通讯系统中针对同层干扰环境对微小型基地台功率控制与用户位置推荐演算法 =Femtocell Power Control and User Location Recommendation Algorithm for Co-Tier Interference Environment in LTE Communication System