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The Knuth-Yao Quadrangle-Inequality Speedup is a Consequence of Total-Monotonicity ∗ (2009)

Abstract
There exist several general techniques in the literature for speeding up naive implementations of dynamic programming. Two of the best known are the Knuth-Yao quadrangle inequality speedup and the SMAWK algorithm for finding the row-minima of totally monotone matrices. Although both of these techniques use a quadrangle inequality and seem similar they are actually quite different and have been used differently in the literature. In this paper we show that the Knuth-Yao technique is actually a direct consequence of total monotonicity. As well as providing new derivations of the Knuth-Yao result, this also permits to solve the Knuth-Yao problem directly using the SMAWK algorithm. Another consequence of this approach is a method for solving online versions of problems with the Knuth-Yao property. The online algorithms given here are asymptotically as fast as the best previously known static ones. For example, the Knuth-Yao technique speeds up the standard dynamic program for finding the optimal binary search tree of n elements from Θ(n 3) down to O(n 2), and the results in this paper allow construction of an optimal binary search tree in an online fashion (adding a node to the left or the right of the current nodes at each step) in O(n) time per step.

Publication details
Download http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.144.7060
Source http://www.cse.ust.hk/~golin/pubs/KY_BGLZ.pdf
Contributors CiteSeerX
Repository CiteSeerX - Scientific Literature Digital Library and Search Engine (United States)
Type text
Language English
Relation 10.1.1.57.2018, 10.1.1.7.5815, 10.1.1.34.4882, 10.1.1.106.1673