Problem 46: Fast JL Transform for Sparse Vectors
Suggested by | Jelani Nelson |
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Source | Bertinoro 2011 |
Short link | https://sublinear.info/46 |
Consider a distribution over linear mappings A from R^d to R^k, k=O(\log (1/P)/\epsilon^2). We say that it has an (\epsilon, P)-JL property if for any vector x \in R^d we have \|Ax\|_2 = (1 \pm \epsilon) \|x\|_2 with probability 1-P.
Question: Can we construct a distribution with this property such that the matrix-vector product Ax can be evaluated in time (s+k)\cdot \operatorname{polylog}(d) time given an s-sparse x?
Background: Such an algorithm is not known even for s=d (unless k is larger [AilonL-11], [KrahmerW-11]).
Question: Provide an explicit construction of a distribution with the (\epsilon, P)-JL property such that the random matrix A can be generated using O(\log (d/P)) bits.