13 citations · 40 across the 25 of their papers we have counts for
3 papers · 1 filter
Finite-dimensional Gaussian approximation with linear inequality constraints
Andrés F. López-Lopera, François Bachoc, Nicolas Durrande +1
Introducing inequality constraints in Gaussian process (GP) models can lead to more realistic uncertainties in learning a great variety of real-world problems. We consider the fini…
On the validity of parametric block correlation matrices with constant within and between group correlations
O Roustant, Y Deville
We consider the set Bp of parametric block correlation matrices with p blocks of various (and possibly different) sizes, whose diagonal blocks are compound symmetry (CS) correlatio…
On the choice of the low-dimensional domain for global optimization via random embeddings
Mickaël Binois, David Ginsbourger, Olivier Roustant
The challenge of taking many variables into account in optimization problems may be overcome under the hypothesis of low effective dimensionality. Then, the search of solutions can…