Hanbyul Lee

2 accepted papers

2024

Support Recovery in Sparse PCA with General Missing Data

UAI 2024poster

We analyze a sparse PCA algorithm for incomplete and noisy data without any specific model assumption on the data missing scheme. We utilize a graphical approach to characterize general missing patterns, which enables us to analyze the effect of structural properties of missing patterns on the solva…

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2022

Support Recovery in Sparse PCA with Incomplete Data

Hanbyul Lee, Qifan Song, Jean Honorio

NeurIPS 2022accept

We study a practical algorithm for sparse principal component analysis (PCA) of incomplete and noisy data. Our algorithm is based on the semidefinite program (SDP) relaxation of the non-convex $l_1$-regularized PCA problem. We provide theoretical and experimental evidence that SDP enables us to exac…

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