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Temporal Logic Point Processes
Shuang Li · Lu Wang · Ruizhi Zhang · xiaofu Chang · Xuqin Liu · Yao Xie · Yuan Qi · Le Song

Tue Jul 14 01:00 PM -- 01:45 PM & Wed Jul 15 12:00 AM -- 12:45 AM (PDT) @

We propose a modeling framework for event data and aim to answer questions such as {\it when} and {\it why} the next event would happen. Our proposed model excels in small data regime with the ability to incorporate domain knowledge in terms of logic rules. We model the dynamics of the event starts and ends via intensity function with the structures informed by a set of first-order temporal logic rules. Using the softened representation of temporal relations, and a weighted combination of logic rules, our probabilistic model can deal with uncertainty in events. Furthermore, many well-known point processes (e.g., Hawkes process, self-correcting point process) can be interpreted as special cases of our model given simple temporal logic rules. Our model, therefore, riches the family of point processes. We derive a maximum likelihood estimation procedure for our model and show that it can lead to accurate predictions when data are sparse and domain knowledge is critical.

Author Information

Shuang Li (Harvard University)
Lu Wang (East China Normal University)
Ruizhi Zhang (University of Nebraska-Lincoln)
xiaofu Chang (Ant Financial Services Group)
Xuqin Liu (Ant Financial Services Group)
Yao Xie (Georgia Institute of Technology)

Yao Xie is an Assistant Professor and Harold R. and Mary Anne Nash Early Career Professor in the H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology. She received her Ph.D. in Electrical Engineering (minor in Mathematics) from Stanford University in 2011. Prior joining Georgia Tech in 2013, she worked as a Research Scientist at Duke University. Her research interests are statistics, signal processing, and machine learning. She received a Best Student Paper Award at Annual Asilomar Conference on Signals, Systems and Computers in 2005, Finalist of Best Student Paper Award in ICASSP Conference in 2007, the Stanford Graduate Fellowship in 2007-2010, the Wen-Yuan Pan Scholarship in 2007, co-author of the Finalist for the INFORMS QSR Student Paper Competition, and the National Science Foundation (NSF) CAREER Award in 2017.

Yuan Qi (Ant Financial Services Group)
Le Song (Georgia Institute of Technology)

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