4 citations · 4 across the 4 of their papers we have counts for
3 papers · 1 filter
Efficient and Scalable Kernel Matrix Approximations using Hierarchical Decomposition
Keerthi Gaddameedi, Severin Reiz, Tobias Neckel +1
With the emergence of Artificial Intelligence, numerical algorithms are moving towards more approximate approaches. For methods such as PCA or diffusion maps, it is necessary to co…
Fast Approximation of the Gauss-Newton Hessian Matrix for the Multilayer Perceptron
Chao Chen, Severin Reiz, Chenhan Yu +2
We introduce a fast algorithm for entry-wise evaluation of the Gauss-Newton Hessian (GNH) matrix for the fully-connected feed-forward neural network. The algorithm has a precomputa…
Geometry-Oblivious FMM for Compressing Dense SPD Matrices
Chenhan D. Yu, James Levitt, Severin Reiz +1
We present GOFMM (geometry-oblivious FMM), a novel method that creates a hierarchical low-rank approximation, "compression," of an arbitrary dense symmetric positive definite (SPD)…