Asynchronous peer-to-peer data mining with stochastic gradient descent

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

Volumn 6852 LNCS, Issue PART 1, 2011, Pages 528-540

  Ormándi, Róbert ^a   Hegedus, István ^a   Jelasity, Márk ^a  

^a UNIVERSITY OF SZEGED   (Hungary)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM SCHEMES; BENCHMARK DATASETS; BITTORRENT; COMMUNICATION COMPLEXITY; COMMUNICATION MODELS; DISTRIBUTED DATA; DISTRIBUTED DATA MINING; GENERIC APPROACH; GLOBAL MODELS; LARGE AMOUNTS OF DATA; LEARNING MODELS; LOCAL ALGORITHM; MACHINE LEARNING METHODS; PEER TO PEER; QUALITY MODELS; RANDOM WALK; STOCHASTIC GRADIENT DESCENT;

DATA MINING; DISTRIBUTED COMPUTER SYSTEMS; INFORMATION THEORY; LEARNING ALGORITHMS; LEARNING SYSTEMS; STOCHASTIC MODELS; STOCHASTIC SYSTEMS; TIME VARYING NETWORKS;

PEER TO PEER NETWORKS;

EID: 80052387251     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-23400-2_49     Document Type: Conference Paper

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