Learning Granger Causality for Hawkes Processes
Authors: Hongteng Xu, Mehrdad Farajtabar, Hongyuan Zha
ICML 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments on both synthetic and real-world data show that our method can learn the Granger causality graph and the triggering patterns of the Hawkes processes simultaneously. |
| Researcher Affiliation | Academia | Hongteng Xu HXU42@GATECH.EDU School of ECE, Georgia Institute of Technology; Mehrdad Farajtabar MEHRDAD@GATECH.EDU College of Computing, Georgia Institute of Technology; Hongyuan Zha ZHA@CC.GATECH.EDU College of Computing, Georgia Institute of Technology |
| Pseudocode | Yes | Algorithm 1 Learning Hawkes Processes (MLE-SGLP); Algorithm 2 Selecting basis functions |
| Open Source Code | No | The paper does not contain any statements or links indicating that open-source code for the methodology is provided. |
| Open Datasets | Yes | We test our algorithm on the IPTV viewing record data set (Luo et al., 2015). |
| Dataset Splits | No | The paper mentions training and testing sets ('C = {50, ..., 250} sequences are chosen randomly as training set while the rest 250 sequences are chosen as testing set.') but does not explicitly describe a validation set or its split. |
| Hardware Specification | No | The paper mentions a 'PC with 16GB memory' in the context of a competitor's algorithm running out of memory, not as a specification for the hardware used in their own experiments. |
| Software Dependencies | No | The paper does not provide specific software names with version numbers that would be needed to replicate the experiment. |
| Experiment Setup | Yes | We set αS = 10, αG = 100, αP = 1000. In all trials, Gaussian basis functions are used, whose number and bandlimit are decided by Algorithm 2. We set the time length of impact function to be 8 days... and the number of samples M = 576... |