scholarly journals Applications of Generating Functions to Stochastic Processes and to the Complexity of the Knapsack Problem

2021 ◽  
Author(s):  
Jorma Jormakka ◽  
Sourangshu Ghosh
Keyword(s):  
Stochastic Process ◽  
Stochastic Processes ◽  
Polynomial Time ◽  
Knapsack Problem ◽  
Generating Functions ◽  
General Theorem ◽  
Main Idea ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Linear Transform

The paper describes a method of solving some stochastic processes using generating functions. A general theorem of generating functions of a particular type is derived. A generating function of this type is applied to a stochastic process yielding polynomial time algorithms for certain partitions. The method is generalized to a stochastic process describing a rather general linear transform. Finally, the main idea of the method is used in deriving a theoretical polynomial time algorithm to the knapsack problem.

A Polynomial-Time Algorithm for the Knapsack Problem with Two Variables

1976 ◽  
Vol 23 (1) ◽  
pp. 147-154 ◽  
Author(s):  
D. S. Hirschberg ◽  
C. K. Wong
Keyword(s):  
Polynomial Time ◽  
Knapsack Problem ◽  
Polynomial Time Algorithm ◽  
Time Algorithm

Efficient Processing of XML Tree Pattern Queries

2006 ◽  
Vol 10 (5) ◽  
pp. 738-743 ◽  
Author(s):  
Yangjun Chen ◽  
◽  
Dunren Che ◽  
Keyword(s):  
Dynamic Programming ◽  
Polynomial Time ◽  
Main Idea ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
The Other ◽  
Tree Pattern ◽  
Efficient Processing

In this paper, we present a polynomial-time algorithm for TPQ (tree pattern queries) minimization without XML constraints involved. The main idea of the algorithm is a dynamic programming strategy to find all the matching subtrees within a TPQ. A matching subtree implies a redundancy and should be removed in such a way that the semantics of the original TPQ is not damaged. Our algorithm consists of two parts: one for subtree recognization and the other for subtree deletion. Both of them needs only O(<I>n</I>2) time, where <I>n</I> is the number of nodes in a TPQ.

scholarly journals Computing the Period of an Ehrhart Quasi-Polynomial

10.37236/1931 ◽  
2005 ◽  
Vol 12 (1) ◽  
Author(s):  
Kevin Woods
Keyword(s):  
Polynomial Time ◽  
Generating Functions ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Minimum Period ◽  
Rational Generating Functions ◽  
Rational Polytope

If $P\subset {\Bbb R}^d$ is a rational polytope, then $i_P(t):=\#(tP\cap {\Bbb Z}^d)$ is a quasi-polynomial in $t$, called the Ehrhart quasi-polynomial of $P$. A period of $i_P(t)$ is ${\cal D}(P)$, the smallest ${\cal D}\in {\Bbb Z}_+$ such that ${\cal D}\cdot P$ has integral vertices. Often, ${\cal D}(P)$ is the minimum period of $i_P(t)$, but, in several interesting examples, the minimum period is smaller. We prove that, for fixed $d$, there is a polynomial time algorithm which, given a rational polytope $P\subset{\Bbb R}^d$ and an integer $n$, decides whether $n$ is a period of $i_P(t)$. In particular, there is a polynomial time algorithm to decide whether $i_P(t)$ is a polynomial. We conjecture that, for fixed $d$, there is a polynomial time algorithm to compute the minimum period of $i_P(t)$. The tools we use are rational generating functions.

Learning Importance of Preferences

10.29007/v68w ◽  
2018 ◽  
Author(s):  
Ying Zhu ◽  
Mirek Truszczynski
Keyword(s):  
Polynomial Time ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Scoring Rules ◽  
Np Hard ◽  
Individual Preferences

We study the problem of learning the importance of preferences in preference profiles in two important cases: when individual preferences are aggregated by the ranked Pareto rule, and when they are aggregated by positional scoring rules. For the ranked Pareto rule, we provide a polynomial-time algorithm that finds a ranking of preferences such that the ranked profile correctly decides all the examples, whenever such a ranking exists. We also show that the problem to learn a ranking maximizing the number of correctly decided examples (also under the ranked Pareto rule) is NP-hard. We obtain similar results for the case of weighted profiles when positional scoring rules are used for aggregation.

scholarly journals Polynomial Time Algorithm for Min-Ranks of Graphs with Simple Tree Structures

Algorithmica ◽  
2013 ◽  
Vol 71 (1) ◽  
pp. 152-180 ◽  
Author(s):  
Son Hoang Dau ◽  
Yeow Meng Chee
Keyword(s):  
Polynomial Time ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Tree Structures ◽  
Simple Tree
Sign in / Sign up

Export Citation Format

Share Document