3 papers
math.ST2026
Network Signflip Parallel Analysis for Selecting the Embedding Dimension
David Hong, Joshua Cape
The paper proposes a data‑driven spectral technique called NetFlipPA that determines how many dimensions to keep when embedding large heterogeneous networks by comparing eigenvalue…
math.ST2026
Selecting the number of components in PCA via random signflips
David Hong, Yue Sheng, Edgar Dobriban
Principal component analysis (PCA) is a foundational tool in modern data analysis, and a crucial step in PCA is selecting the number of components to keep. However, classical selec…
math.NA2026
Generalized Canonical Polyadic Tensor Decompositions with General Symmetry
Alex Mulrooney, David Hong
Canonical Polyadic (CP) tensor decomposition is a workhorse algorithm for discovering underlying low-dimensional structure in tensor data. This is accomplished in conventional CP d…