Discrepancy sets and pseudorandom generators for combinatorial rectangles

Authors:
R. Armoni;M. Saks;A. Wigderson;Shiyu Zhou
Affiliations:
-;-;-;-
Venue:
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
Year:
1996

Citing 0
Cited 4

Approximating hyper-rectangles: learning and pseudo-random sets

STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Small Pseudo-Random Sets Yield Hard Functions: New Tight Explict Lower Bounds for Branching Programs

ICAL '99 Proceedings of the 26th International Colloquium on Automata, Languages and Programming
Pseudorandom generators for combinatorial shapes

Proceedings of the forty-third annual ACM symposium on Theory of computing
Pseudorandom generators for combinatorial checkerboards

Computational Complexity

Quantified Score

Hi-index	0.00

Visualization

Abstract

A common subproblem of DNF approximate counting and derandomizing RL is the discrepancy problem for combinatorial rectangles. We explicitly construct a poly(n)-size sample space that approximates the volume of any combinatorial rectangle in [n]/sup n/ to within o(1) error. The construction extends the previous techniques for the analogous hitting set problem, most notably via discrepancy preserving reductions.