Hierarchical Compound Poisson Factorization
Authors: Mehmet Basbug, Barbara Engelhardt
ICML 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We compare HCPF with HPF on nine discrete and three continuous data sets and conclude that HCPF captures the relationship between sparsity and response better than HPF. |
| Researcher Affiliation | Academia | Mehmet E. Basbug MEHMETBASBUG@YAHOO.COM Princeton University, 35 Olden St., Princeton, NJ 08540 USA Barbara E. Engelhardt BEE@PRINCETON.EDU Princeton University, 35 Olden St., Princeton, NJ 08540 USA |
| Pseudocode | Yes | Algorithm 1 SVI for HCPF |
| Open Source Code | No | The paper does not provide a link to its source code or explicitly state that the code is publicly available. |
| Open Datasets | Yes | The rating data sets include amazon fine food ratings (Mc Auley & Leskovec, 2013), movielens (Harper & Konstan, 2015), netflix (Bell & Koren, 2007) and yelp... social media activity data sets (wordpress and tencent) (Niu et al., 2012)... biochemistry data set (merck) (Ma et al., 2015)... echonest (Bertin-Mahieux et al., 2011)... genomics data set (geuvadis) (Lappalainen et al., 2013). |
| Dataset Splits | Yes | We held out 20% and 1% of the non-missing entries for testing (Ytest NM) and validation, respectively. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware used to run the experiments (e.g., CPU, GPU models, or memory). |
| Software Dependencies | No | The paper does not provide specific version numbers for any software dependencies or libraries used in the experiments. |
| Experiment Setup | Yes | In HCPF, we fix K = 160, ξ = 0.7 and τ = 10, 000 after an empirical study on smaller data sets. To set hyperparameters θ and κ, we use the maximum likelihood estimates of the element distribution parameters on the non-missing entries. ... We then used E[nui] to set the factorization hyperparameters η, ζ, ρ, ϱ, ω, ϖ. To create heavy tails and uninformative gamma priors, we set ϖ = ϱ = 0.1 and ω = ρ = 0.01. |