Sublinear time algorithms
Sublinear Time Algorithms Page 1 Copyright © by SIAM. Unauthorized reproduction of this article
is prohibited. SIAM J. DISCRETE MATH. c 2011 Society for Industrial and Applied Mathematics …
is prohibited. SIAM J. DISCRETE MATH. c 2011 Society for Industrial and Applied Mathematics …
New diameter-reducing shortcuts and directed hopsets: Breaking the barrier
For an n-vertex digraph G=(V, E), a shortcut set is a (small) subset of edges H taken from the
transitive closure of G that, when added to G guarantees that the diameter of G∪ H is small …
transitive closure of G that, when added to G guarantees that the diameter of G∪ H is small …
Testing and reconstruction of Lipschitz functions with applications to data privacy
A function f:D→R is Lipschitz if d_R(f(x),f(y))≦d_D(x,y) for all x,y in D, where d_R and d_D
denote the distance metrics on the range and domain of f, respectively. We initiate the study …
denote the distance metrics on the range and domain of f, respectively. We initiate the study …
Optimal bounds for monotonicity and Lipschitz testing over hypercubes and hypergrids
The problem of monotonicity testing over the hypergrid and its special case, the hypercube,
is a classic question in property testing. We are given query access to f:[k] n-> R (for some …
is a classic question in property testing. We are given query access to f:[k] n-> R (for some …
[KİTAP][B] Property Testing: Problems and Techniques
A Bhattacharyya, Y Yoshida - 2022 - books.google.com
This book introduces important results and techniques in property testing, where the goal is
to design algorithms that decide whether their input satisfies a predetermined property in …
to design algorithms that decide whether their input satisfies a predetermined property in …
Finding options that minimize planning time
We formalize the problem of selecting the optimal set of options for planning as that of
computing the smallest set of options so that planning converges in less than a given …
computing the smallest set of options so that planning converges in less than a given …
A polynomial lower bound for testing monotonicity
We show that every algorithm for testing n-variate Boolean functions for monotonicityhas
query complexity Ω (n 1/4). All previous lower bounds for this problem were designed for …
query complexity Ω (n 1/4). All previous lower bounds for this problem were designed for …
Approximating the distance to monotonicity of boolean functions
We design a nonadaptive algorithm that, given oracle access to a function which is‐far from
monotone, makes poly queries and returns an estimate that, with high probability, is an …
monotone, makes poly queries and returns an estimate that, with high probability, is an …
Efficient and simple algorithms for fault-tolerant spanners
It was recently shown that a version of the greedy algorithm gives a construction of fault-
tolerant spanners that is size-optimal, at least for vertex faults. However, the algorithm to …
tolerant spanners that is size-optimal, at least for vertex faults. However, the algorithm to …
Monotonicity testing and shortest-path routing on the cube
We study the problem of monotonicity testing over the hypercube. As previously observed in
several works, a positive answer to a natural question about routing properties of the …
several works, a positive answer to a natural question about routing properties of the …