Search Results for author: Ilse C. F. Ipsen

Found 4 papers, 0 papers with code

Stochastic Rounding Implicitly Regularizes Tall-and-Thin Matrices

no code implementations18 Mar 2024 Gregory Dexter, Christos Boutsikas, Linkai Ma, Ilse C. F. Ipsen, Petros Drineas

Motivated by the popularity of stochastic rounding in the context of machine learning and the training of large-scale deep neural network models, we consider stochastic nearness rounding of real matrices $\mathbf{A}$ with many more rows than columns.

Probabilistic Iterative Methods for Linear Systems

no code implementations23 Dec 2020 Jon Cockayne, Ilse C. F. Ipsen, Chris J. Oates, Tim W. Reid

This paper presents a probabilistic perspective on iterative methods for approximating the solution $\mathbf{x}_* \in \mathbb{R}^d$ of a nonsingular linear system $\mathbf{A} \mathbf{x}_* = \mathbf{b}$.

Uncertainty Quantification

A Projector-Based Approach to Quantifying Total and Excess Uncertainties for Sketched Linear Regression

no code implementations17 Aug 2018 Jocelyn T. Chi, Ilse C. F. Ipsen

To answer this question, we present a projector-based approach to sketched linear regression that is exact and that requires minimal assumptions on the sketching matrix.

Dimensionality Reduction regression

Randomized Approximation of the Gram Matrix: Exact Computation and Probabilistic Bounds

no code implementations5 Oct 2013 John T. Holodnak, Ilse C. F. Ipsen

Given a real matrix A with n columns, the problem is to approximate the Gram product AA^T by c << n weighted outer products of columns of A.

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