High-performance geometric algorithms for sparse computation in big data analytics

Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017

Volumn 2018-January, Issue , 2017, Pages 546-555

  Baumann, Philipp ^a   Hochbaum, Dorit S ^b   Spaen, Quico ^b  

^a UNIVERSITY OF BERN   (Switzerland)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Big data; computational geometry; similarity based machine learning; sparse computation; sparsification

Indexed keywords

BIG DATA; COMPUTATIONAL GEOMETRY; DATA ANALYTICS; LEARNING ALGORITHMS; NEAREST NEIGHBOR SEARCH;

DATA SET; GEOMETRIC ALGORITHM; GRID BLOCKS; LARGE SCALE DATA SETS; LOW-DIMENSIONAL SPACES; SPARSIFICATION; UNSUPERVISED MACHINE LEARNING; VERY LARGE DATUM;

MACHINE LEARNING;

EID: 85047800735     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BigData.2017.8257970     Document Type: Conference Paper

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