Recurrent marked temporal point processes: Embedding event history to vector

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn 13-17-August-2016, Issue , 2016, Pages 1555-1564

  Du, Nan ^a   Dai, Hanjun ^a   Trivedi, Rakshit ^a   Upadhyay, Utkarsh ^b   Gomez Rodriguez, Manuel ^b   Song, Le ^a  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^b MAX PLANCK INSTITUTE FOR SOFTWARE SYSTEMS   (Germany)

Author keywords

Marked temporal point process; Recurrent neural network; Stochastic process

Indexed keywords

DATA MINING; DYNAMICS; RANDOM PROCESSES; RECURRENT NEURAL NETWORKS; STOCHASTIC SYSTEMS;

INDEPENDENTLY AND IDENTICALLY DISTRIBUTED; INTENSITY FUNCTIONS; MATHEMATICAL FRAMEWORKS; NONLINEAR FUNCTIONS; POINT PROCESS; PREDICTIVE PERFORMANCE; REAL-WORLD DATASETS; STOCHASTIC GRADIENT ALGORITHMS;

STOCHASTIC MODELS;

EID: 84985027657     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2939672.2939875     Document Type: Conference Paper

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