Summary of Masked Language Modeling Becomes Conditional Density Estimation For Tabular Data Synthesis, by Seunghwan An et al.
Masked Language Modeling Becomes Conditional Density Estimation for Tabular Data Synthesis
by Seunghwan An, Gyeongdong Woo, Jaesung Lim, ChangHyun Kim, Sungchul Hong, Jong-June Jeon
First submitted to arxiv on: 31 May 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Computation and Language (cs.CL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed MaCoDE method generates synthetic data for heterogeneous tabular datasets with high machine learning utility (MLu) by redefining the consecutive multi-class classification task of Masked Language Modeling (MLM) as histogram-based non-parametric conditional density estimation. This approach enables estimating conditional densities across arbitrary combinations of target and conditional variables, bridging the theoretical gap between distributional learning and MLM. The MaCoDE model is evaluated on 10 real-world datasets, demonstrating its ability to adjust data privacy levels easily without re-training. Furthermore, it shows effectiveness in handling training datasets with missing values, including multiple imputations. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a new way to make synthetic data for mixed-type datasets that machines can learn from well. They do this by changing the task of language models into one that estimates conditional densities. This helps them create data that’s realistic and useful for machine learning. The method, called MaCoDE, is tested on 10 real-world datasets and shows it can adjust privacy levels without re-training. It also works well with missing values in the training data. |
Keywords
» Artificial intelligence » Classification » Density estimation » Machine learning » Synthetic data
