LINEAR TIME RECOGNITION AND OPTIMIZATIONS FOR WEAK-BISPLIT GRAPHS, BI-COGRAPHS AND BIPARTITE P6-FREE GRAPHS

2003 ◽  
Vol 14 (01) ◽  
pp. 107-136 ◽  
Author(s):  
V. GIAKOUMAKIS ◽  
J. M. VANHERPE
Keyword(s):  
Optimization Problems ◽  
Linear Time ◽  
Bipartite Graphs ◽  
Efficient Solutions ◽  
Canonical Decomposition ◽  
Decomposition Scheme ◽  
Linear Time Algorithms

In [7] was introduced a new decomposition scheme for bipartite graphs that was called canonical decomposition. Weak-bisplit graphs are totally decomposable following this decomposition. We give here linear time algorithms for the recognition of weak-bisplit graphs as well as for two subclasses of this class, the P6-free bipartite graphs and the bi-cographs. Our algorithms extends the technics developped in [2] for cographs's recognition. We conclude by presenting efficient solutions for some optimization problems when dealing with weak-bisplit graphs.

Fast and simple algorithms for counting dominating sets in distance-hereditary graphs

2020 ◽  
pp. 2150012
Author(s):  
Min-Sheng Lin
Keyword(s):  
Linear Time ◽  
Bipartite Graphs ◽  
Chordal Graphs ◽  
Dominating Sets ◽  
Complete Problem ◽  
Split Graphs ◽  
Linear Time Algorithms ◽  
Chordal Bipartite Graphs

Counting dominating sets (DSs) in a graph is a #P-complete problem even for chordal bipartite graphs and split graphs, which are both subclasses of weakly chordal graphs. This paper investigates this problem for distance-hereditary graphs, which is another known subclass of weakly chordal graphs. This work develops linear-time algorithms for counting DSs and their two variants, total DSs and connected DSs in distance-hereditary graphs.

BIPARTITE GRAPHS TOTALLY DECOMPOSABLE BY CANONICAL DECOMPOSITION

1999 ◽  
Vol 10 (04) ◽  
pp. 513-533 ◽  
Author(s):  
JEAN-LUC FOUQUET ◽  
VASSILIS GIAKOUMAKIS ◽  
JEAN-MARIE VANHERPE
Keyword(s):  
Optimization Problems ◽  
Bipartite Graphs ◽  
Canonical Decomposition ◽  
Forbidden Subgraphs ◽  
Polynomial Solutions ◽  
The Family ◽  
Np Complete ◽  
General Graphs

We describe here a technique of decomposition of bipartite graphs which seems to be as interesting within this context as the well known modular and split techniques for the decomposition of general graphs. In particular, we characterize by forbidden subgraphs the family of bipartite graphs which are totally decomposable (i.e. reducible to single vertices) with respect to our decomposition. This family contains previously known families of graphs such as bicographs and P6-free bipartite graphs. As an application we provide polynomial solutions of optimization problems, some of them being NP-complete for general bipartite graphs.

scholarly journals Almost Linear Time Algorithms for Minsum k-Sink Problems on Dynamic Flow Path Networks

2021 ◽  
Author(s):  
Yuya Higashikawa ◽  
Naoki Katoh ◽  
Junichi Teruyama ◽  
Koji Watase
Keyword(s):  
Linear Time ◽  
Flow Path ◽  
Dynamic Flow ◽  
Linear Time Algorithms

scholarly journals Linear-Time Algorithms for Tree Root Problems

Algorithmica ◽  
2013 ◽  
Vol 71 (2) ◽  
pp. 471-495 ◽  
Author(s):  
Maw-Shang Chang ◽  
Ming-Tat Ko ◽  
Hsueh-I Lu
Keyword(s):  
Linear Time ◽  
Linear Time Algorithms

FAULT TOLERANT ROUTING IN HYPERCUBES AND STAR GRAPHS

1996 ◽  
Vol 06 (01) ◽  
pp. 127-136 ◽  
Author(s):  
QIAN-PING GU ◽  
SHIETUNG PENG
Keyword(s):  
Free Path ◽  
Fault Tolerant ◽  
Linear Time ◽  
Time Efficiency ◽  
Routing Problem ◽  
Star Graphs ◽  
Linear Time Algorithms ◽  
Better Than

In this paper, we give two linear time algorithms for node-to-node fault tolerant routing problem in n-dimensional hypercubes Hn and star graphs Gn. The first algorithm, given at most n−1 arbitrary fault nodes and two non-fault nodes s and t in Hn, finds a fault-free path s→t of length at most [Formula: see text] in O(n) time, where d(s, t) is the distance between s and t. Our second algorithm, given at most n−2 fault nodes and two non-fault nodes s and t in Gn, finds a fault-free path s→t of length at most d(Gn)+3 in O(n) time, where [Formula: see text] is the diameter of Gn. When the time efficiency of finding the routing path is more important than the length of the path, the algorithms in this paper are better than the previous ones.

scholarly journals Entropy-Penalized Semidefinite Programming

2019 ◽  
Author(s):  
Mikhail Krechetov ◽  
Jakub Marecek ◽  
Yury Maximov ◽  
Martin Takac
Keyword(s):  
Machine Learning ◽  
Time Complexity ◽  
Optimization Problems ◽  
Linear Time ◽  
Broad Class ◽  
Low Rank ◽  
Learning Problems ◽  
Unified Framework ◽  
Gradient Computation ◽  
Machine Learning Applications

Low-rank methods for semi-definite programming (SDP) have gained a lot of interest recently, especially in machine learning applications. Their analysis often involves determinant-based or Schatten-norm penalties, which are difficult to implement in practice due to high computational efforts. In this paper, we propose Entropy-Penalized Semi-Definite Programming (EP-SDP), which provides a unified framework for a broad class of penalty functions used in practice to promote a low-rank solution. We show that EP-SDP problems admit an efficient numerical algorithm, having (almost) linear time complexity of the gradient computation; this makes it useful for many machine learning and optimization problems. We illustrate the practical efficiency of our approach on several combinatorial optimization and machine learning problems.

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