On the Model Shrinkage Effect of Gamma Process Edge Partition Models
Authors: Iku Ohama, Issei Sato, Takuya Kida, Hiroki Arimura
NeurIPS 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We experimentally confirmed that the model shrinkage of the proposed models works well and that the IDEPM indicated state-of-the-art performance in generalization ability, link prediction accuracy, mixing efficiency, and convergence speed. |
| Researcher Affiliation | Collaboration | Iku Ohama Panasonic Corp., Japan Issei Sato The Univ. of Tokyo, Japan Takuya Kida Hiroki Arimura Hokkaido Univ., Japan |
| Pseudocode | Yes | Sampling z: Given m, similar to the Chinese restaurant process (CRP) [15], the posterior probability that zi,j,s is assigned to k is given as follows: P(zi,j,s = k | z\(ijs), m) ... Sampling m: Given z, posteriors for the φ and ψ are simulated as ... Therefore, similar to the sampler for the EPM [8], we can update m as follows: mi,j, | φ, ψ, λ δ(0) if xi,j = 0, ZTP(PK+ k=1 φi,kψj,kλk) if xi,j = 1, {mi,j,k}K+ k=1 | mi,j, , φ, ψ, λ Multinomial |
| Open Source Code | No | The paper does not provide concrete access to source code or explicitly state its release. |
| Open Datasets | Yes | The first dataset was the Enron [16] dataset, which comprises e-mails sent between 149 Enron employees. ... For larger dataset, we used the Movie Lens [17] dataset, which comprises five-point scale ratings of movies submitted by users. |
| Dataset Splits | Yes | Furthermore, all reported measurements were averaged values obtained by 10-fold cross validation. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory, or cloud instance types) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers. |
| Experiment Setup | Yes | We ran 600 Gibbs iterations for each model on each dataset and used the final 100 iterations to calculate the measurements. Furthermore, all reported measurements were averaged values obtained by 10-fold cross validation. ... For the purpose of fair comparison, we set hyper-hyperparameters as e0 = f0 = 0.01 throughout the experiments. |