Download or read book Graph Mining written by Deepayan Chakrabarti and published by Morgan & Claypool Publishers. This book was released on 2012-10-01 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: What does the Web look like? How can we find patterns, communities, outliers, in a social network? Which are the most central nodes in a network? These are the questions that motivate this work. Networks and graphs appear in many diverse settings, for example in social networks, computer-communication networks (intrusion detection, traffic management), protein-protein interaction networks in biology, document-text bipartite graphs in text retrieval, person-account graphs in financial fraud detection, and others. In this work, first we list several surprising patterns that real graphs tend to follow. Then we give a detailed list of generators that try to mirror these patterns. Generators are important, because they can help with "what if" scenarios, extrapolations, and anonymization. Then we provide a list of powerful tools for graph analysis, and specifically spectral methods (Singular Value Decomposition (SVD)), tensors, and case studies like the famous "pageRank" algorithm and the "HITS" algorithm for ranking web search results. Finally, we conclude with a survey of tools and observations from related fields like sociology, which provide complementary viewpoints. Table of Contents: Introduction / Patterns in Static Graphs / Patterns in Evolving Graphs / Patterns in Weighted Graphs / Discussion: The Structure of Specific Graphs / Discussion: Power Laws and Deviations / Summary of Patterns / Graph Generators / Preferential Attachment and Variants / Incorporating Geographical Information / The RMat / Graph Generation by Kronecker Multiplication / Summary and Practitioner's Guide / SVD, Random Walks, and Tensors / Tensors / Community Detection / Influence/Virus Propagation and Immunization / Case Studies / Social Networks / Other Related Work / Conclusions

Download or read book Spectral Algorithms written by Ravindran Kannan and published by Now Publishers Inc. This book was released on 2009 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spectral methods refer to the use of eigenvalues, eigenvectors, singular values and singular vectors. They are widely used in Engineering, Applied Mathematics and Statistics. More recently, spectral methods have found numerous applications in Computer Science to "discrete" as well as "continuous" problems. Spectral Algorithms describes modern applications of spectral methods, and novel algorithms for estimating spectral parameters. The first part of the book presents applications of spectral methods to problems from a variety of topics including combinatorial optimization, learning and clustering. The second part of the book is motivated by efficiency considerations. A feature of many modern applications is the massive amount of input data. While sophisticated algorithms for matrix computations have been developed over a century, a more recent development is algorithms based on "sampling on the fly" from massive matrices. Good estimates of singular values and low rank approximations of the whole matrix can be provably derived from a sample. The main emphasis in the second part of the book is to present these sampling methods with rigorous error bounds. It also presents recent extensions of spectral methods from matrices to tensors and their applications to some combinatorial optimization problems.

Download or read book Approximation Randomization and Combinatorial Optimization Algorithms and Techniques written by Josep Diaz and published by Springer Science & Business Media. This book was released on 2006-08-11 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the joint refereed proceedings of the 9th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2006 and the 10th International Workshop on Randomization and Computation, RANDOM 2006. The book presents 44 carefully reviewed and revised full papers. Among the topics covered are design and analysis of approximation algorithms, hardness of approximation problems, small spaces and data streaming algorithms, embeddings and metric space methods, and more.

Download or read book Approximation Randomization and Combinatorial Optimization Algorithms and Techniques written by Prasad Raghavendra and published by Springer. This book was released on 2013-08-16 with total page 728 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 16th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2013, and the 17th International Workshop on Randomization and Computation, RANDOM 2013, held in August 2013 in the USA. The total of 48 carefully reviewed and selected papers presented in this volume consist of 23 APPROX papers selected out of 46 submissions, and 25 RANDOM papers selected out of 52 submissions. APPROX 2013 focuses on algorithmic and complexity theoretic issues relevant to the development of efficient approximate solutions to computationally difficult problems, while RANDOM 2013 focuses on applications of randomness to computational and combinatorial problems.

Download or read book Algorithm Engineering written by Lasse Kliemann and published by Springer. This book was released on 2016-11-10 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithm Engineering is a methodology for algorithmic research that combines theory with implementation and experimentation in order to obtain better algorithms with high practical impact. Traditionally, the study of algorithms was dominated by mathematical (worst-case) analysis. In Algorithm Engineering, algorithms are also implemented and experiments conducted in a systematic way, sometimes resembling the experimentation processes known from fields such as biology, chemistry, or physics. This helps in counteracting an otherwise growing gap between theory and practice.

Download or read book Graph Partitioning and Graph Clustering written by David A. Bader and published by American Mathematical Soc.. This book was released on 2013-03-18 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph partitioning and graph clustering are ubiquitous subtasks in many applications where graphs play an important role. Generally speaking, both techniques aim at the identification of vertex subsets with many internal and few external edges. To name only a few, problems addressed by graph partitioning and graph clustering algorithms are: What are the communities within an (online) social network? How do I speed up a numerical simulation by mapping it efficiently onto a parallel computer? How must components be organized on a computer chip such that they can communicate efficiently with each other? What are the segments of a digital image? Which functions are certain genes (most likely) responsible for? The 10th DIMACS Implementation Challenge Workshop was devoted to determining realistic performance of algorithms where worst case analysis is overly pessimistic and probabilistic models are too unrealistic. Articles in the volume describe and analyze various experimental data with the goal of getting insight into realistic algorithm performance in situations where analysis fails.

Download or read book Pattern Recognition written by Katrin Franke and published by Springer Science & Business Media. This book was released on 2006-09-11 with total page 790 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 28th Symposium of the German Association for Pattern Recognition, DAGM 2006. The book presents 32 revised full papers and 44 revised poster papers together with 5 invited papers. Topical sections include image filtering, restoration and segmentation, shape analysis and representation, recognition, categorization and detection, computer vision and image retrieval, machine learning and statistical data analysis, biomedical data analysis, and more.

Download or read book Experimental Algorithms written by Jan Vahrenhold and published by Springer Science & Business Media. This book was released on 2009-05-22 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th International Symposium on Experimental and Efficient Algorithms, SEA 2009, held in Dortmund, Germany, in June 2009. The 23 revised full papers were carefully reviewed and selected from 64 submissions and present current research on experimental evaluation and engineering of algorithms, as well as in various aspects of computational optimization and its applications. Contributions are supported by experimental evaluation, methodological issues in the design and interpretation of experiments, the use of (meta-) heuristics, or application-driven case studies that deepen the understanding of a problem's complexity.

Download or read book Faster Algorithms Via Approximation Theory written by Sushant Sachdeva and published by . This book was released on 2014-03-28 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Faster Algorithms via Approximation Theory illustrates how classical and modern techniques from approximation theory play a crucial role in obtaining results that are relevant to the emerging theory of fast algorithms. The key lies in the fact that such results imply faster ways to approximate primitives such as products of matrix functions with vectors and, to compute matrix eigenvalues and eigenvectors, which are fundamental to many spectral algorithms. The first half of the book is devoted to the ideas and results from approximation theory that are central, elegant, and may have wider applicability in theoretical computer science. These include not only techniques relating to polynomial approximations but also those relating to approximations by rational functions and beyond. The remaining half illustrates a variety of ways that these results can be used to design fast algorithms. Faster Algorithms via Approximation Theory is self-contained and should be of interest to researchers and students in theoretical computer science, numerical linear algebra, and related areas.

Download or read book Graph Symmetry written by Gena Hahn and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: The last decade has seen two parallel developments, one in computer science, the other in mathematics, both dealing with the same kind of combinatorial structures: networks with strong symmetry properties or, in graph-theoretical language, vertex-transitive graphs, in particular their prototypical examples, Cayley graphs. In the design of large interconnection networks it was realised that many of the most fre quently used models for such networks are Cayley graphs of various well-known groups. This has spawned a considerable amount of activity in the study of the combinatorial properties of such graphs. A number of symposia and congresses (such as the bi-annual IWIN, starting in 1991) bear witness to the interest of the computer science community in this subject. On the mathematical side, and independently of any interest in applications, progress in group theory has made it possible to make a realistic attempt at a complete description of vertex-transitive graphs. The classification of the finite simple groups has played an important role in this respect.

Download or read book Graph Representation Learning written by William L. William L. Hamilton and published by Springer Nature. This book was released on 2022-06-01 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Random Walks and Diffusion written by Open University Course Team and published by . This book was released on 2009-10-21 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This block explores the diffusion equation which is most commonly encountered in discussions of the flow of heat and of molecules moving in liquids, but diffusion equations arise from many different areas of applied mathematics. As well as considering the solutions of diffusion equations in detail, we also discuss the microscopic mechanism underlying the diffusion equation, namely that particles of matter or heat move erratically. This involves a discussion of elementary probability and statistics, which are used to develop a description of random walk processes and of the central limit theorem. These concepts are used to show that if particles follow random walk trajectories, their density obeys the diffusion equation.

Download or read book 40th ACM International Symposium on Theory of Computing written by STOC (40, 2008, Victoria, British Columbia) and published by . This book was released on 2008 with total page 832 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Algorithms for Sensor Systems written by Antonio Fernández Anta and published by Springer. This book was released on 2017-12-30 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes revised selected papers from the 13th International Symposium on Algorithms and Experiments for Wireless Sensor Networks, ALGOSENSORS 2017, held in Vienna, in September 2017. The 17 full papers presented in this volume were carefully reviewed and selected from 30 submissions. ALGOSENSORS is an international symposium dedicated to the algorithmic aspects of wireless networks. Originally focused on sensor networks, it now covers algorithmic issues arising in wireless networks of all types of computational entities, static or mobile, including sensor networks, sensor-actuator networks, autonomous robots. The focus is on the design and analysis of algorithms, models of computation, and experimental analysis.

Download or read book Lx B Laplacian Solvers and Their Algorithmic Applications written by Nisheeth K Vishnoi and published by . This book was released on 2013-03-01 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Illustrates the emerging paradigm of employing Laplacian solvers to design novel fast algorithms for graph problems through a small but carefully chosen set of examples. This monograph can be used as the text for a graduate-level course, or act as a supplement to a course on spectral graph theory or algorithms.

Download or read book Chordal Graphs and Semidefinite Optimization written by Lieven Vandenberghe and published by Foundations and Trends (R) in Optimization. This book was released on 2015-04-30 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covers the theory and applications of chordal graphs, with an emphasis on algorithms developed in the literature on sparse Cholesky factorization. It shows how these techniques can be applied in algorithms for sparse semidefinite optimization, and points out the connections with related topics outside semidefinite optimization.

Download or read book Iterative Methods for Sparse Linear Systems written by Yousef Saad and published by SIAM. This book was released on 2003-04-01 with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematics of Computing -- General.