4 papers
Approximate maximum likelihood estimators for linear regression with design matrix uncertainty
Richard J Clancy, Stephen Becker
In this paper we consider regression problems subject to arbitrary noise in the operator or design matrix. This characterization appropriately models many physical phenomena with u…
Robust Least Squares for Quantized Data Matrices
Richard Clancy, Stephen Becker
In this paper we formulate and solve a robust least squares problem for a system of linear equations subject to quantization error in the data matrix. Ordinary least squares fails…
Locality-sensitive hashing in function spaces
Will Shand, Stephen Becker
We discuss the problem of performing similarity search over function spaces. To perform search over such spaces in a reasonable amount of time, we use {\it locality-sensitive hashi…
Guarantees for the Kronecker Fast Johnson-Lindenstrauss Transform Using a Coherence and Sampling Argument
Osman Asif Malik, Stephen Becker
In the recent paper [Jin, Kolda & Ward, arXiv:1909.04801], it is proved that the Kronecker fast Johnson-Lindenstrauss transform (KFJLT) is, in fact, a Johnson-Lindenstrauss transfo…