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05/10/2023
Maximum likelihood thresholds of generic linear concentration models
The maximum likelihood threshold of a statistical model is the minimum n...
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10/20/2022
Computing maximum likelihood thresholds using graph rigidity
The maximum likelihood threshold (MLT) of a graph G is the minimum numbe...
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04/26/2022
Lattices Without a Big Constant and With Noise
We show how Frieze's analysis of subset sum solving using lattices can b...
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08/04/2021
Maximum likelihood thresholds via graph rigidity
The maximum likelihood threshold (MLT) of a graph G is the minimum numbe...
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03/04/2014
Matroid Regression
We propose an algebraic combinatorial method for solving large sparse li...
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02/01/2014
Dual-to-kernel learning with ideals
In this paper, we propose a theory which unifies kernel learning and sym...
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02/21/2013
Obtaining error-minimizing estimates and universal entry-wise error bounds for low-rank matrix completion
We propose a general framework for reconstructing and denoising single e...
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02/12/2013
Coherence and sufficient sampling densities for reconstruction in compressed sensing
We give a new, very general, formulation of the compressed sensing probl...
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11/17/2012