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- W2951219878 abstract "An oblivious subspace embedding (OSE) for some eps, delta in (0,1/3) and d <= m <= n is a distribution D over R^{m x n} such that for any linear subspace W of R^n of dimension d, Pr_{Pi ~ D}(for all x in W, (1-eps) |x|_2 = 1 - delta. We prove that any OSE with delta < 1/3 must have m = Omega((d + log(1/delta))/eps^2), which is optimal. Furthermore, if every Pi in the support of D is sparse, having at most s non-zero entries per column, then we show tradeoff lower bounds between m and s." @default.
- W2951219878 created "2019-06-27" @default.
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- W2951219878 date "2013-08-15" @default.
- W2951219878 modified "2023-09-28" @default.
- W2951219878 title "Lower bounds for oblivious subspace embeddings" @default.
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