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Found 4 papers, 3 papers with code
On the Usefulness of Synthetic Tabular Data Generation
Despite recent advances in synthetic data generation, the scientific community still lacks a unified consensus on its usefulness.
Black-box Coreset Variational Inference
Recent advances in coreset methods have shown that a selection of representative datapoints can replace massive volumes of data for Bayesian inference, preserving the relevant statistical information and significantly accelerating subsequent downstream tasks.
Bayesian Pseudocoresets
Standard Bayesian inference algorithms are prohibitively expensive in the regime of modern large-scale data.
$β$-Cores: Robust Large-Scale Bayesian Data Summarization in the Presence of Outliers
Modern machine learning applications should be able to address the intrinsic challenges arising over inference on massive real-world datasets, including scalability and robustness to outliers.
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