25 citations · 25 across the 1 of their papers we have counts for
3 papers
cs.LG2022★ 25 cited
Graph Neural Networks with Adaptive Readouts
David Buterez, Jon Paul Janet, Steven J. Kiddle +2
An effective aggregation of node features into a graph-level representation via readout functions is an essential step in numerous learning tasks involving graph neural networks. T…
stat.ML2018
Scalable Learning in Reproducing Kernel Krein Spaces
Dino Oglic, Thomas Gärtner
We provide the first mathematically complete derivation of the Nyström method for low-rank approximation of indefinite kernels and propose an efficient method for finding an approx…
stat.ML2018
Towards A Unified Analysis of Random Fourier Features
Zhu Li, Jean-Francois Ton, Dino Oglic +1
Random Fourier features is a widely used, simple, and effective technique for scaling up kernel methods. The existing theoretical analysis of the approach, however, remains focused…