10 citations · 17 across the 2 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2015★ 7 cited
Diverse Landmark Sampling from Determinantal Point Processes for Scalable Manifold Learning
Christian Wachinger, Polina Golland
High computational costs of manifold learning prohibit its application for large point sets. A common strategy to overcome this problem is to perform dimensionality reduction on se…
cs.LG2014★ 10 cited
Diversifying Sparsity Using Variational Determinantal Point Processes
Nematollah Kayhan Batmanghelich, Gerald Quon, Alex Kulesza +3
We propose a novel diverse feature selection method based on determinantal point processes (DPPs). Our model enables one to flexibly define diversity based on the covariance of fea…