AI RESEARCH
From DPPs to $k$-DPPs: identifiability analysis via spectral decomposition
arXiv CS.LG
•
ArXi:2605.25526v1 Announce Type: cross We study the geometry of determinantal point processes (DPPs) through the spectral decomposition $L=U\Lambda U^{\top}$. The spectrum $\Lambda$ governs the cardinality distribution via elementary symmetric polynomials, while the eigenspace orientation $U$ governs the conditional law within each fixed-cardinality stratum.