Mining of Massive Datasets Jure Leskovec Stanford Univ.

First Page		Document Content
Date: 2014-04-03 15:20:09 Information retrieval Search algorithms Parallel computing MinHash MapReduce Jaccard index Nearest neighbor search Locality-sensitive hashing Collaborative filtering Information science Science Computing		Mining of Massive Datasets Jure Leskovec Stanford Univ. Add to Reading List Source URL: infolab.stanford.edu Download Document from Source Website File Size: 82,83 KB Share Document on Facebook

	Millisort: An Experiment in Granular Computing Seo Jin Park with Yilong Li, Collin Lee and John Ousterhout Massively Parallel Granular Computing DocID: 1xUyt - View Document
	arXiv:1803.04432v1 [cs.DC] 12 MarMemory Models for C/C++ Programmers Manuel P¨oter Jesper Larsson Tr¨aff Research Group Parallel Computing DocID: 1xTxL - View Document
	FEIIC International Journal of Engineering and Technology, Vol. 13, No.2, 2016, ppSURVEY ANALYSIS ON THE EMBEDDED TCPP CURRICULUM IN PARALLEL AND DISTRIBUTED COMPUTING COURSE DocID: 1vq34 - View Document
	Parallel Computing with IPython: an application to air pollution modeling DocID: 1vlLp - View Document
	Multi-EM Multi-Method Inversion to Determine the Electrical Conductivity Distribution of the Subsurface Using Parallel Computing Architectures Multi-EM DocID: 1uVPD - View Document