Polynomial Time Algorithms for Dual Volume Sampling

NeurIPS 2017 Chengtao LiStefanie JegelkaSuvrit Sra

We study dual volume sampling, a method for selecting k columns from an n x m short and wide matrix (n <= k <= m) such that the probability of selection is proportional to the volume spanned by the rows of the induced submatrix. This method was proposed by Avron and Boutsidis (2013), who showed it to be a promising method for column subset selection and its multiple applications... (read more)

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