Faster parameterized algorithm for pumpkin vertex deletion set

A directed graph $G$ is called a pumpkin if $G$ is a union of induced paths with a common start vertex $s$ and a common end vertex $t$, and the internal vertices of every two paths are disjoint. We give an algorithm that given a directed graph $G$ and an integer $k$, decides whether a pumpkin can be obtained from $G$ by deleting at most $k$ vertices. The algorithm runs in $O^*(2^k)$ time

Weighted vertex cover on graphs with maximum degree 3

We give a parameterized algorithm for weighted vertex cover on graphs with maximum degree 3 whose time complexity is $O^*(1.402^t)$, where $t$ is the minimum size of a vertex cover of the input graph

Succinct data structure for dynamic trees with faster queries

Navarro and Sadakane [TALG 2014] gave a dynamic succinct data structure for storing an ordinal tree. The structure supports tree queries in either $O(\log n/\log\log n)$ or $O(\log n)$ time, and insertion or deletion of a single node in $O(\log n)$ time. In this paper we improve the result of Navarro and Sadakane by reducing the time complexities of some queries (e.g.\ degree and level\_ancestor) from $O(\log n)$ to $O(\log n/\log\log n)$

Parameterized algorithm for 3-path vertex cover

In the 3-path vertex cover problem, the input is an undirected graph $G$ and an integer $k$. The goal is to decide whether there is a set of vertices $S$ of size at most $k$ such that every path with 3 vertices in $G$ contains at least one vertex of $S$. In this paper we give parameterized algorithm for 3-path cover whose time complexity is $O^*(1.713^k)$. Our algorithm is faster than previous algorithms for this problem

An O^*(2.619^k) algorithm for 4-path vertex cover

In the 4-path vertex cover problem, the input is an undirected graph $G$ and an integer $k$. The goal is to decide whether there is a set of vertices $S$ of size at most $k$ such that every path with 4 vertices in $G$ contains at least one vertex of $S$. In this paper we give a parameterized algorithm for 4-path vertex cover whose time complexity is $O^*(2.619^k)$

Succinct representation of labeled trees

We give a representation for labeled ordered trees that supports labeled queries such as finding the i-th ancestor of a node with a given label. Our representation is succinct, namely the redundancy is small-o of the optimal space for storing the tree. This improves the representation of He et al. which is succinct unless the entropy of the labels is small

Faster parameterized algorithm for Cluster Vertex Deletion

In the Cluster Vertex Deletion problem the input is a graph $G$ and an integer $k$. The goal is to decide whether there is a set of vertices $S$ of size at most $k$ such that the deletion of the vertices of $S$ from $G$ results a graph in which every connected component is a clique. We give an algorithm for Cluster Vertex Deletion whose running time is $O^*(1.811^k)$

Faster deterministic parameterized algorithm for k-Path

In the k-Path problem, the input is a directed graph $G$ and an integer $k\geq 1$, and the goal is to decide whether there is a simple directed path in $G$ with exactly $k$ vertices. We give a deterministic algorithm for k-Path with time complexity $O^*(2.554^k)$. This improves the previously best deterministic algorithm for this problem of Zehavi [ESA 2015] whose time complexity is $O^*(2.597^k)$. The technique used by our algorithm can also be used to obtain faster deterministic algorithms for k-Tree, r-Dimensional k-Matching, Graph Motif, and Partial Cover

l-path vertex cover is easier than l-hitting set for small l

In the $l$-path vertex cover problem the input is an undirected graph $G$ and an integer $k$. The goal is to decide whether there is a set of vertices $S$ of size at most $k$ such that $G-S$ does not contain a path with $l$ vertices. In this paper we give parameterized algorithms for $l$-path vertex cover for $l = 5,6,7$, whose time complexities are $O^*(3.945^k)$, $O^*(4.947^k)$, and $O^*(5.951^k)$, respectively.Comment: arXiv admin note: text overlap with arXiv:1901.0760

Representation of ordered trees with a given degree distribution

The degree distribution of an ordered tree $T$ with $n$ nodes is $\vec{n} = (n_0,\ldots,n_{n-1})$, where $n_i$ is the number of nodes in $T$ with $i$ children. Let $\mathcal{N}(\vec{n})$ be the number of trees with degree distribution $\vec{n}$. We give a data structure that stores an ordered tree $T$ with $n$ nodes and degree distribution $\vec{n}$ using $\log \mathcal{N}(\vec{n})+O(n/\log^t n)$ bits for every constant $t$. The data structure answers tree queries in constant time. This improves the current data structures with lowest space for ordered trees: The structure of Jansson et al.\ [JCSS 2012] that uses $\log\mathcal{N}(\vec{n})+O(n\log\log n/\log n)$ bits, and the structure of Navarro and Sadakane [TALG 2014] that uses $2n+O(n/\log^t n)$ bits for every constant $t$