20 citations · 76 across the 13 of their papers we have counts for
Showing stat.MLShow all
2 papers · 1 filter
stat.ML2018★ 18 cited
Determinantal Point Processes for Coresets
Nicolas Tremblay, Simon Barthelmé, Pierre-Olivier Amblard
When faced with a data set too large to be processed all at once, an obvious solution is to retain only part of it. In practice this takes a wide variety of different forms, and am…
stat.ML2013★ 1 cited
Visualizing the Effects of a Changing Distance on Data Using Continuous Embeddings
Gina Gruenhage, Manfred Opper, Simon Barthelme
Most Machine Learning (ML) methods, from clustering to classification, rely on a distance function to describe relationships between datapoints. For complex datasets it is hard to…