Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Ridge Regression with Frequent Directions: Statistical and Optimization
  Perspectives   Despite its impressive theory \& practical performance, Frequent Directions
(\acrshort{fd}) has not been widely adopted for large-scale regression tasks.
Prior work has shown randomized sketches (i) perform worse in estimating the
covariance matrix of the data than \acrshort{fd}; (ii) incur high error when
estimating the bias and/or variance on sketched ridge regression. We give the
first constant factor relative error bounds on the bias \& variance for
sketched ridge regression using \acrshort{fd}. We complement these statistical
results by showing that \acrshort{fd} can be used in the optimization setting
through an iterative scheme which yields high-accuracy solutions. This improves
on randomized approaches which need to compromise the need for a new sketch
every iteration with speed of convergence. In both settings, we also show using
\emph{Robust Frequent Directions} further enhances performance.

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The categories of this paper are: mtrl-th
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The categories of this paper are: quant-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: plasm-ph
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The categories of this paper are: atom-ph
11
The categories of this paper are: hep-lat
7
The categories of this paper are: hep-th
10
The categories of this paper are: q-bio
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The categories of this paper are: math-ph
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The categories of this paper are: eess
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The categories of this paper are: gr-qc
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The categories of this paper are: adap-org
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The categories of this paper are: chao-dyn
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The categories of this paper are: funct-an
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The categories of this paper are: astro-ph
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The categories of this paper are: alg-geom