Nov 8, 2018 · We study the complexity of sampling from a distribution over all subsets of rows where the probability of a subset is proportional to the squared volume of the ...
Determinantal point processes (DPP) form a family of distributions sampling diverse subsets of points from a given domain, where the diversity is measured by ...
We study the complexity of sampling from a distribution over all subsets of rows where the probability of a subset is proportional to the squared volume of the ...
Duration: 10:38
Posted: Sep 9, 2019
Posted: Sep 9, 2019
2023. Fast determinantal point processes via distortion-free intermediate sampling. M Dereziński. Conference on Learning Theory, 1029-1049, 2019. 34, 2019.
Fast determinantal point processes via distortion-free intermediate sampling. In Alina Beygelzimer and Daniel Hsu, editors, Proceedings of the Thirty-Second ...
Nov 23, 2018 · Michal Derezinski: Fast determinantal point processes via distortion-free intermediate sampling. CoRR abs/1811.03717 (2018).
Some common techniques to determine k include performing a density-based analysis of the data [9], or selecting k that minimizes the Bayesian information.
Missing: intermediate | Show results with:intermediate
Determinantal point processes (DPPs) are a useful probabilistic model for selecting a small diverse subset out of a large collection of items, with applications ...
Feb 21, 2019 · Determinantal point processes (DPP) form a family of distributions sampling diverse subsets of points from a given domain, where the diversity ...