Predicting User Activity Level In Point Processes With Mass Transport Equation
Authors: Yichen Wang, Xiaojing Ye, Hongyuan Zha, Le Song
NeurIPS 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In this section, we evaluate the predictive performance of HYBRID in two real world applications in Section 5 and a synthetic dataset. We use the following metrics: (i) Mean Average Percentage Error (MAPE). (ii) Rank correlation. |
| Researcher Affiliation | Collaboration | College of Computing, Georgia Institute of Technology School of Mathematics, Georgia State University Ant Financial {yichen.wang}@gatech.edu, xye@gsu.edu {zha,lsong}@cc.gatech.edu |
| Pseudocode | Yes | Algorithm 1: CONDITIONAL MASS FUNCTION |
| Open Source Code | No | The paper does not contain any explicit statements about releasing open-source code for the described methodology, nor does it provide any links to a code repository. |
| Open Datasets | Yes | We use a Twitter dataset [2] that contains 280,000 users with 550,000 tweet, retweet, and link creation events during Sep. 21 30, 2012. This data is previously used to validate the network co-evolution model [12]. ... In the recommendation system setting, we use two datasets from [25]. The IPTV dataset contains 7,100 users watching history of 436 TV programs in 11 months, with around 2M events. The Reddit dataset contains online discussions of 1,000 users in 1,403 groups, with 10,000 discussion events. |
| Dataset Splits | No | The paper mentions 'training data' and 'test data' splits (e.g., 'We use p proportion of total data as the training data to learn parameters of all methods, and the rest as test data'), but it does not explicitly specify a 'validation' dataset split. |
| Hardware Specification | Yes | We use the machine with 16 cores, 2.4 GHz Intel Core i5 CPU and 64 GB memory. |
| Software Dependencies | No | The paper mentions using the 'ODE45 solver in MATLAB', but it does not provide specific version numbers for MATLAB or any other software dependencies, which are necessary for reproducible setup. |
| Experiment Setup | Yes | To choose a proper M, we generate samples from the point process. Suppose the largest number of events in the samples is L, we set M = 2L such that it is reasonably large. ... We use the ODE45 solver in MATLAB and choose the stage s = 4 for RK. ... We use 103 samples for HYBRID and compare it with the following the state of the art. MC-1E3. It is the MC sampling method with 103 samples (same as these for HYBRID), and MC-1E6 uses 106 samples. |