Fast Sampling for Strongly Rayleigh Measures with Application to Determinantal Point Processes

Abstract

In this note we consider sampling from (non-homogeneous) strongly Rayleigh probability measures. As an important corollary, we obtain a fast mixing Markov Chain sampler for Determinantal Point Processes.

References in corpus (3)

• Determinantal point processes for machine learning
• Determinantal Probability: Basic Properties and Conjectures
• The Kadison-Singer Problem for Strongly Rayleigh Measures and Applications to Asymmetric TSP

Cited by in corpus (1)

• Learning from DPPs via Sampling: Beyond HKPV and symmetry