Browsing by Subject "Multi-task Multi-dimensional Hawkes Process (MMHP)"

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    Multi-Task Multi-Dimensional Hawkes Processes for Modeling Event Sequences
    (ACM, 2015-07) Luo, Dixin; Xu, Hongteng; Zhen, Yi; Ning, Xia; Zha, Hongyuan; Yang, Xiaokang; Zhang, Wenjun; Department of Computer and Information Science, School of Science
    We propose a Multi-task Multi-dimensional Hawkes Process (MMHP) for modeling event sequences where there exist multiple triggering patterns within sequences and structures across sequences. MMHP is able to model the dynamics of multiple sequences jointly by imposing structural constraints and thus systematically uncover clustering structure among sequences. We propose an effective and robust optimization algorithm to learn MMHP models, which takes advantage of alternating direction method of multipliers (ADMM), majorization minimization and Euler-Lagrange equations. Our experimental results demonstrate that MMHP performs well on both synthetic and real data.