Search Results for author: Simon Barthelmé

Found 4 papers, 0 papers with code

Determinantal Point Processes for Coresets

no code implementations23 Mar 2018 Nicolas Tremblay, Simon Barthelmé, Pierre-Olivier Amblard

We apply our results to both the k-means and the linear regression problems, and give extensive empirical evidence that the small additional computational cost of DPP sampling comes with superior performance over its iid counterpart.

Point Processes

Asymptotic Equivalence of Fixed-size and Varying-size Determinantal Point Processes

no code implementations5 Mar 2018 Simon Barthelmé, Pierre-Olivier Amblard, Nicolas Tremblay

In this work we show that as the size of the ground set grows, $k$-DPPs and DPPs become equivalent, meaning that their inclusion probabilities converge.

Point Processes

Graph sampling with determinantal processes

no code implementations5 Mar 2017 Nicolas Tremblay, Pierre-Olivier Amblard, Simon Barthelmé

For large graphs, ie, in cases where the graph's spectrum is not accessible, we investigate, both theoretically and empirically, a sub-optimal but much faster DPP based on loop-erased random walks on the graph.

Graph Sampling Point Processes

The Poisson transform for unnormalised statistical models

no code implementations11 Jun 2014 Simon Barthelmé, Nicolas Chopin

Here we show that inferring the parameters of a unnormalised model on a space $\Omega$ can be mapped onto an equivalent problem of estimating the intensity of a Poisson point process on $\Omega$.

Cannot find the paper you are looking for? You can Submit a new open access paper.