Federated Latent Dirichlet Allocation: A Local Differential Privacy Based Framework
Authors: Yansheng Wang, Yongxin Tong, Dingyuan Shi6283-6290
AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments on three open datasets verified the effectiveness of our solution. |
| Researcher Affiliation | Academia | Yansheng Wang, Yongxin Tong, Dingyuan Shi SKLSDE Lab, BDBC, School of Computer Science and Engineering and IRI, Beihang University, China {arthur wang, yxtong, chnsdy}@buaa.edu.cn |
| Pseudocode | Yes | Algorithm. 1 shows the details of local sampling. Algorithm. 2 shows the details of global integration. Algorithm. 3 shows our RRP mechanism. |
| Open Source Code | No | The paper does not provide any statement or link indicating that open-source code for the methodology is available. |
| Open Datasets | Yes | We use three open datasets: Reviews 2, Emails 3 and Sentiments 4 (Maas et al. 2011). The dataset Emails contains 33,716 spam/non-spam emails with M = 150 and |V| = 3309. The dataset Sentiments has 50,000 highly polar movie reviews with positive/negative sentiments, with M = 150 and |V| = 22574. |
| Dataset Splits | Yes | We split training data and test data by 4 : 1 for logistic regression and train both data for 100 iterations with the same solver. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., CPU, GPU models, memory) used for the experiments. It only mentions general terms like 'computer clusters'. |
| Software Dependencies | No | The paper does not specify software dependencies with version numbers (e.g., Python 3.x, PyTorch 1.x, specific library versions). |
| Experiment Setup | Yes | Parameter settings. We randomly sample 1K, 5K and 3K instances respectively from Reviews, Emails and Sentiments for evaluation. The default ϵ is 7.5 for all datasets and the default K is 20 for Reviews, 30 for Emails and 50 for Sentiments. |