Pointer chasing via triangular discrimination
Keyword(s):
AbstractWe prove an essentially sharp $\tilde \Omega (n/k)$ lower bound on the k-round distributional complexity of the k-step pointer chasing problem under the uniform distribution, when Bob speaks first. This is an improvement over Nisan and Wigderson’s $\tilde \Omega (n/{k^2})$ lower bound, and essentially matches the randomized lower bound proved by Klauck. The proof is information-theoretic, and a key part of it is using asymmetric triangular discrimination instead of total variation distance; this idea may be useful elsewhere.
2017 ◽
Vol 2017
◽
pp. 1-11
◽
2002 ◽
Vol 34
(03)
◽
pp. 609-625
◽
2016 ◽
Vol 52
(4)
◽
pp. 1614-1640
◽
2018 ◽
Vol 52
(4)
◽
pp. 662-679
◽
2014 ◽
Vol 59
(9)
◽
pp. 2353-2368
◽
1995 ◽
Vol 32
(03)
◽
pp. 768-776
◽
Keyword(s):