A parallel nonnegative tensor factorization algorithm for mining global climate data

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5545 LNCS, Issue PART 2, 2009, Pages 405-415

  Zhang, Qiang ^a   Berry, Michael W ^b   Lamb, Brian T ^b   Samuel, Tabitha ^b  

^a WAKE FOREST UNIVERSITY HEALTH SCIENCES   (United States)

^b University of Tennessee   (United States)

Author keywords

Data mining; Global climate; Nonnegative tensor factorization; Parallel computation

Indexed keywords

CLUSTER NODES; COMPUTER SCIENTISTS; DATA SETS; GLOBAL CLIMATE; GLOBAL CLIMATES; LARGE DATASETS; MAXIMAL DEGREE; MEMORY USE; NONNEGATIVE TENSOR FACTORIZATION; NONNEGATIVE TENSOR FACTORIZATIONS; NUMERICAL EXPERIMENTS; PARALLEL COMPUTATION; PARALLELIZING; SEA SURFACE TEMPERATURES; STRUCTURAL RELATIONSHIP;

ATMOSPHERIC TEMPERATURE; FACTORIZATION; MINING; NASA; PARALLEL ALGORITHMS;

TENSORS;

EID: 70149088187     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-01973-9_45     Document Type: Conference Paper

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