11,238 research outputs found
Hardness and inapproximability results for minimum verification set and minimum path decision tree problems
Minimization of decision trees is a well studied problem. In this work, we introduce two new problems related to minimization of decision trees. The problems are called minimum verification set (MinVS) and minimum path decision tree (MinPathDT) problems. Decision tree problems ask the question "What is the unknown given object?". MinVS problem on the other hand asks the question "Is the unknown object z?", for a given object z. Hence it is not an identification, but rather a verification problem. MinPathDT problem aims to construct a decision tree where only the cost of the root-to-leaf path corresponding to a given object is minimized, whereas decision tree problems in general try to minimize the overall cost of decision trees considering all the
objects. Therefore, MinVS and MinPathDT are seemingly easier problems.
However, in this work we prove that MinVS and MinPathDT problems are both NP-complete and cannot be approximated within a factor in o(lg n) unless P = NP
-Approximation Algorithm for Directed Steiner Tree: A Tight Quasi-Polynomial-Time Algorithm
In the Directed Steiner Tree (DST) problem we are given an -vertex
directed edge-weighted graph, a root , and a collection of terminal
nodes. Our goal is to find a minimum-cost arborescence that contains a directed
path from to every terminal. We present an -approximation algorithm for DST that runs in
quasi-polynomial-time. By adjusting the parameters in the hardness result of
Halperin and Krauthgamer, we show the matching lower bound of
for the class of quasi-polynomial-time
algorithms. This is the first improvement on the DST problem since the
classical quasi-polynomial-time approximation algorithm by
Charikar et al. (The paper erroneously claims an approximation due
to a mistake in prior work.)
Our approach is based on two main ingredients. First, we derive an
approximation preserving reduction to the Label-Consistent Subtree (LCST)
problem. The LCST instance has quasi-polynomial size and logarithmic height. We
remark that, in contrast, Zelikovsky's heigh-reduction theorem used in all
prior work on DST achieves a reduction to a tree instance of the related Group
Steiner Tree (GST) problem of similar height, however losing a logarithmic
factor in the approximation ratio. Our second ingredient is an LP-rounding
algorithm to approximately solve LCST instances, which is inspired by the
framework developed by Rothvo{\ss}. We consider a Sherali-Adams lifting of a
proper LP relaxation of LCST. Our rounding algorithm proceeds level by level
from the root to the leaves, rounding and conditioning each time on a proper
subset of label variables. A small enough (namely, polylogarithmic) number of
Sherali-Adams lifting levels is sufficient to condition up to the leaves
Digraph Complexity Measures and Applications in Formal Language Theory
We investigate structural complexity measures on digraphs, in particular the
cycle rank. This concept is intimately related to a classical topic in formal
language theory, namely the star height of regular languages. We explore this
connection, and obtain several new algorithmic insights regarding both cycle
rank and star height. Among other results, we show that computing the cycle
rank is NP-complete, even for sparse digraphs of maximum outdegree 2.
Notwithstanding, we provide both a polynomial-time approximation algorithm and
an exponential-time exact algorithm for this problem. The former algorithm
yields an O((log n)^(3/2))- approximation in polynomial time, whereas the
latter yields the optimum solution, and runs in time and space O*(1.9129^n) on
digraphs of maximum outdegree at most two. Regarding the star height problem,
we identify a subclass of the regular languages for which we can precisely
determine the computational complexity of the star height problem. Namely, the
star height problem for bideterministic languages is NP-complete, and this
holds already for binary alphabets. Then we translate the algorithmic results
concerning cycle rank to the bideterministic star height problem, thus giving a
polynomial-time approximation as well as a reasonably fast exact exponential
algorithm for bideterministic star height.Comment: 19 pages, 1 figur
Combinatorial optimization problems in self-assembly
Self-assembly is the ubiquitous process by which simple objects autonomously assemble into intricate complexes. It has been suggested that intricate self-assembly processes will ultimately be used in circuit fabrication, nano-robotics, DNA computation, and amorphous computing. In this paper, we study two combinatorial optimization problems related to efficient self-assembly of shapes in the Tile Assembly Model of self-assembly proposed by Rothemund and Winfree [18]. The first is the Minimum Tile Set Problem, where the goal is to find the smallest tile system that uniquely produces a given shape. The second is the Tile Concentrations Problem, where the goal is to decide on the relative concentrations of different types of tiles so that a tile system assembles as quickly as possible. The first problem is akin to finding optimum program size, and the second to finding optimum running time for a "program" to assemble the shape.Self-assembly is the ubiquitous process by which simple objects autonomously assemble into intricate complexes. It has been suggested that intricate self-assembly processes will ultimately be used in circuit fabrication, nano-robotics, DNA computation, and amorphous computing. In this paper, we study two combinatorial optimization problems related to efficient self-assembly of shapes in the Tile Assembly Model of self-assembly proposed by Rothemund and Winfree [18]. The first is the Minimum Tile Set Problem, where the goal is to find the smallest tile system that uniquely produces a given shape. The second is the Tile Concentrations Problem, where the goal is to decide on the relative concentrations of different types of tiles so that a tile system assembles as quickly as possible. The first problem is akin to finding optimum program size, and the second to finding optimum running time for a "program" to assemble the shape. We prove that the first problem is NP-complete in general, and polynomial time solvable on trees and squares. In order to prove that the problem is in NP, we present a polynomial time algorithm to verify whether a given tile system uniquely produces a given shape. This algorithm is analogous to a program verifier for traditional computational systems, and may well be of independent interest. For the second problem, we present a polynomial time -approximation algorithm that works for a large class of tile systems that we call partial order systems
On the Complexity of Searching in Trees: Average-case Minimization
We focus on the average-case analysis: A function w : V -> Z+ is given which
defines the likelihood for a node to be the one marked, and we want the
strategy that minimizes the expected number of queries. Prior to this paper,
very little was known about this natural question and the complexity of the
problem had remained so far an open question.
We close this question and prove that the above tree search problem is
NP-complete even for the class of trees with diameter at most 4. This results
in a complete characterization of the complexity of the problem with respect to
the diameter size. In fact, for diameter not larger than 3 the problem can be
shown to be polynomially solvable using a dynamic programming approach.
In addition we prove that the problem is NP-complete even for the class of
trees of maximum degree at most 16. To the best of our knowledge, the only
known result in this direction is that the tree search problem is solvable in
O(|V| log|V|) time for trees with degree at most 2 (paths).
We match the above complexity results with a tight algorithmic analysis. We
first show that a natural greedy algorithm attains a 2-approximation.
Furthermore, for the bounded degree instances, we show that any optimal
strategy (i.e., one that minimizes the expected number of queries) performs at
most O(\Delta(T) (log |V| + log w(T))) queries in the worst case, where w(T) is
the sum of the likelihoods of the nodes of T and \Delta(T) is the maximum
degree of T. We combine this result with a non-trivial exponential time
algorithm to provide an FPTAS for trees with bounded degree
Ising formulations of many NP problems
We provide Ising formulations for many NP-complete and NP-hard problems,
including all of Karp's 21 NP-complete problems. This collects and extends
mappings to the Ising model from partitioning, covering and satisfiability. In
each case, the required number of spins is at most cubic in the size of the
problem. This work may be useful in designing adiabatic quantum optimization
algorithms.Comment: 27 pages; v2: substantial revision to intro/conclusion, many more
references; v3: substantial revision and extension, to-be-published versio
Hardness measures and resolution lower bounds
Various "hardness" measures have been studied for resolution, providing
theoretical insight into the proof complexity of resolution and its fragments,
as well as explanations for the hardness of instances in SAT solving. In this
report we aim at a unified view of a number of hardness measures, including
different measures of width, space and size of resolution proofs. We also
extend these measures to all clause-sets (possibly satisfiable).Comment: 43 pages, preliminary version (yet the application part is only
sketched, with proofs missing
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