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cs.LG2024
Towards a framework on tabular synthetic data generation: a minimalist approach: theory, use cases, and limitations
Yueyang Shen, Agus Sudjianto, Arun Prakash R +5
We propose and study a minimalist approach towards synthetic tabular data generation. The model consists of a minimalistic unsupervised SparsePCA encoder (with contingent clusterin…
cs.LG2022
Behavior of Hyper-Parameters for Selected Machine Learning Algorithms: An Empirical Investigation
Anwesha Bhattacharyya, Joel Vaughan, Vijayan N. Nair
Hyper-parameters (HPs) are an important part of machine learning (ML) model development and can greatly influence performance. This paper studies their behavior for three algorithm…