1 citations · 2 across the 24 of their papers we have counts for
5 papers · 2 filters
RJD-BASE: Multi-Modal Spectral Clustering via Randomized Joint Diagonalization
Haoze He, Artemis Pados, Daniel Kressner
We revisit the problem of spectral clustering in multimodal settings, where each data modality is encoded as a graph Laplacian. While classical approaches--including joint diagonal…
On the randomized SVD in infinite dimensions
Daniel Kressner, David Persson, André Uschmajew
Randomized methods, such as the randomized SVD (singular value decomposition) and Nyström approximation, are an effective way to compute low-rank approximations of large matrices.…
Lanczos with compression for symmetric matrix Lyapunov equations
Angelo A. Casulli, Francesco Hrobat, Daniel Kressner
This work considers large-scale Lyapunov matrix equations of the form , where is a symmetric positive definite matrix and $\boldsymbol…
Stochastic trace estimation for parameter-dependent matrices applied to spectral density approximation
Fabio Matti, Haoze He, Daniel Kressner +1
Stochastic trace estimation is a well-established tool for approximating the trace of a large symmetric matrix . Several applications involve a matrix that depends…
Compression Properties for large Toeplitz-like matrices
Bernhard Beckermann, Daniel Kressner, Heather Wilber
Toeplitz matrices are abundant in computational mathematics, and there is a rich literature on the development of fast and superfast algorithms for solving linear systems involving…