The Structure of Near-minimum Edge Cuts

The Structure of Near-minimum Edge Cuts
Author: Andras Benczúr
Publisher:
Total Pages: 18
Release: 1994
Genre: Graph theory
ISBN:

Abstract: "Let G be an undirected k-edge connected graph. In this paper we give a representation for all edge cuts with capacity not exceeding roughly (6/5)k. This generalizes the cactus representation (Dinits et al) for all minimum cuts. Karger proved that the number of cuts within a multiplicative factor α of the connectivity is at most O(n[superscript 2α]). We improve this bound to O(n2) for α=6/5. An important corollary of our result is a proof with new insights to the Lovaśz splitting theorem. A splitting of the edge pair us and vs at vertex s means replacing the two edges by uv. A splitting is admissible if it preserves the minimum local edge connectivity of the graph apart from vertex s. In other words, we may split us and vs if there is no set of degree minimum or minimum+1 containing both u and v; this property can be checked by our representation. Our new technique makes it possible to derive structure results of admissible pairs; among others we can show that splittable pairs form a connected graph unless the degree of s is odd or equals 4. We believe that by using our representation it will be possible to improve on results using the cactus or splittings. One such result is the edge augmentation problem where one needs a minimum cardinality edge set which increases the connectivity of the graph. The algorithm of Naor, Gusfield and Martels applies the cactus representation to solve this problem; Frank's algorithm relies on the splitting theorems."

Proceedings of the Sixth Annual ACM-SIAM Symposium on Discrete Algorithms

Proceedings of the Sixth Annual ACM-SIAM Symposium on Discrete Algorithms
Author:
Publisher: SIAM
Total Pages: 668
Release: 1995-01-01
Genre: Computers
ISBN: 9780898713497

The proceedings of the January 1995 symposium, sponsored by the ACM Special Interest Group on Algorithms and Computation Theory and the SIAM Activity Group on Discrete Mathematics, comprise 70 papers. Among the topics: on-line approximate list indexing with applications; finding subsets maximizing minimum structures; register allocation in structured programs; and splay trees for data compression. No index. Annotation copyright by Book News, Inc., Portland, OR

Algorithm Theory - SWAT 2000

Algorithm Theory - SWAT 2000
Author: Magnús M. Halldórsson
Publisher: Springer Science & Business Media
Total Pages: 578
Release: 2000-06-21
Genre: Computers
ISBN: 3540676902

This book constitutes the refereed proceedings of the 7th Scandinavian Workshop on Algorithm Theory, SWAT 2000, held in Bergen, Norway, in July 2000. The 43 revised full papers presented together with 3 invited contributions were carefully reviewed and selected from a total of 105 submissions. The papers are organized in sections on data structures, dynamic partitions, graph algorithms, online algorithms, approximation algorithms, matchings, network design, computational geometry, strings and algorithm engineering, external memory algorithms, optimization, and distributed and fault-tolerant computing.

Discrete Optimization

Discrete Optimization
Author: E. Boros
Publisher: Elsevier
Total Pages: 587
Release: 2003-03-19
Genre: Mathematics
ISBN: 008093028X

One of the most frequently occurring types of optimization problems involves decision variables which have to take integer values. From a practical point of view, such problems occur in countless areas of management, engineering, administration, etc., and include such problems as location of plants or warehouses, scheduling of aircraft, cutting raw materials to prescribed dimensions, design of computer chips, increasing reliability or capacity of networks, etc. This is the class of problems known in the professional literature as "discrete optimization" problems. While these problems are of enormous applicability, they present many challenges from a computational point of view. This volume is an update on the impressive progress achieved by mathematicians, operations researchers, and computer scientists in solving discrete optimization problems of very large sizes. The surveys in this volume present a comprehensive overview of the state of the art in discrete optimization and are written by the most prominent researchers from all over the world. This volume describes the tremendous progress in discrete optimization achieved in the last 20 years since the publication of Discrete Optimization '77, Annals of Discrete Mathematics, volumes 4 and 5, 1979 (Elsevier). It contains surveys of the state of the art written by the most prominent researchers in the field from all over the world, and covers topics like neighborhood search techniques, lift and project for mixed 0-1 programming, pseudo-Boolean optimization, scheduling and assignment problems, production planning, location, bin packing, cutting planes, vehicle routing, and applications to graph theory, mechanics, chip design, etc. Key features: • state of the art surveys • comprehensiveness • prominent authors • theoretical, computational and applied aspects. This book is a reprint of Discrete Applied Mathematics Volume 23, Numbers 1-3

Graph Representation Learning

Graph Representation Learning
Author: William L. William L. Hamilton
Publisher: Springer Nature
Total Pages: 141
Release: 2022-06-01
Genre: Computers
ISBN: 3031015886

Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.

Computing and Combinatorics

Computing and Combinatorics
Author: Takao Asano
Publisher: Springer
Total Pages: 508
Release: 2003-05-21
Genre: Computers
ISBN: 3540486860

The abstracts and papers in this volume were presented at the Fifth Annual International Computing and Combinatorics Conference (COCOON ’99), which was held in Tokyo, Japan from July 26 to 28, 1999. The topics cover most aspects of theoretical computer science and combinatorics pertaining to computing. In response to the call for papers, 88 high-quality extended abstracts were submitted internationally, of which 46 were selected for presentation by the p- gram committee. Every submitted paper was reviewed by at least three program committee members. Many of these papers represent reports on continuing - search, and it is expected that most of them will appear in a more polished and complete form in scienti c journals. In addition to the regular papers, this v- ume contains abstracts of two invited plenary talks by Prabhakar Raghavan and Seinosuke Toda. The conference also included a special talk by Kurt Mehlhorn on LEDA (Library of E cient Data types and Algorithms). The Hao Wang Award (inaugurated at COCOON ’97) is given to honor the paper judged by the program committee to have the greatest scienti c merit. The recipients of the Hao Wang Award 1999 were Hiroshi Nagamochi and Tos- hide Ibaraki for their paper \An Approximation for Finding a Smallest 2-Edge- Connected Subgraph Containing a Speci ed Spanning Tree".