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Article overview
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New Algorithms and Lower Bounds for LIS Estimation | Ilan Newman
; Nithin Varma
; | Date: |
12 Oct 2020 | Abstract: | Estimating the length of the longest increasing subsequence (LIS) in an array
is a problem of fundamental importance. In this paper, we investigate the two
aspects of adaptivity and parameterization in sublinear-time algorithms for LIS
estimation. We first show that adaptivity helps in LIS estimation,
specifically, for every constant $epsilon in (0,1)$, every nonadaptive
algorithm that outputs an estimate of the length of the LIS in an array of
length $n$ to within an additive error of $epsilon cdot n$ has to make
$log^{Omega(log (1/epsilon))} n)$ queries. This is the first lower bound on
LIS estimation that is significantly larger than the query complexity of
testing sortedness. In contrast, there is an adaptive algorithm (Saks, and
Seshadhri; 2017) for the same problem with query complexity polylogarithmic in
$n$.
Next, we design nonadaptive LIS estimation algorithms whose complexity is
parameterized in terms of the number of distinct values $r$ in the array. We
first present a simple algorithm that makes $ ilde{O}(r/epsilon^3)$ queries
and approximates the LIS with an additive error bounded by $epsilon n$. We
then use it to construct a nonadaptive algorithm with query complexity
$ ilde{O}(sqrt{r}/lambda^2)$ that, for an array in which the LIS is of
length at least $lambda n$, outputs a $O(lambda)$ multiplicative
approximation to the length of the LIS. Our algorithm improves upon state of
the art nonadaptive algorithms for LIS estimation (for $r=n$) in terms of
approximation guarantee.
Finally, we describe a nonadaptive erasure-resilient tester for sortedness,
with query complexity $O(log n)$. Our result implies that nonadaptive tolerant
testing is strictly harder than nonadaptive erasure-resilient testing for the
natural property of sortedness, thereby making progress towards solving an open
question (Raskhodnikova, Ron-Zewi, and Varma; 2019). | Source: | arXiv, 2010.05805 | Services: | Forum | Review | PDF | Favorites |
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