Using Additional Information In Streaming Algorithms

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Using Additional Information In Streaming Algorithms

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Author : Raffael Buff
language : en
Publisher: diplom.de
Release Date : 2016-12-08

Using Additional Information In Streaming Algorithms written by Raffael Buff and has been published by diplom.de this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-08 with Computers categories.

Streaming problems are algorithmic problems that are mainly characterized by their massive input streams. Because of these data streams, the algorithms for these problems are forced to be space-efficient, as the input stream length generally exceeds the available storage. The goal of this study is to analyze the impact of additional information (more specifically, a hypothesis of the solution) on the algorithmic space complexities of several streaming problems. To this end, different streaming problems are analyzed and compared. The two problems “most frequent item” and “number of distinct items”, with many configurations of different result accuracies and probabilities, are deeply studied. Both lower and upper bounds for the space and time complexity for deterministic and probabilistic environments are analyzed with respect to possible improvements due to additional information. The general solution search problem is compared to the decision problem where a solution hypothesis has to be satisfied.

Data Streams

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Author : S. Muthukrishnan
language : en
Publisher: Now Publishers Inc
Release Date : 2005

Data Streams written by S. Muthukrishnan and has been published by Now Publishers Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Computers categories.

In the data stream scenario, input arrives very rapidly and there is limited memory to store the input. Algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. In the past few years, a new theory has emerged for reasoning about algorithms that work within these constraints on space, time, and number of passes. Some of the methods rely on metric embeddings, pseudo-random computations, sparse approximation theory and communication complexity. The applications for this scenario include IP network traffic analysis, mining text message streams and processing massive data sets in general. Researchers in Theoretical Computer Science, Databases, IP Networking and Computer Systems are working on the data stream challenges.

Algorithms Advances In Research And Application 2013 Edition

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Author :
language : en
Publisher: ScholarlyEditions
Release Date : 2013-06-21

Algorithms Advances In Research And Application 2013 Edition written by and has been published by ScholarlyEditions this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-21 with Computers categories.

Algorithms—Advances in Research and Application: 2013 Edition is a ScholarlyEditions™ book that delivers timely, authoritative, and comprehensive information about Coloring Algorithm. The editors have built Algorithms—Advances in Research and Application: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Coloring Algorithm in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Algorithms—Advances in Research and Application: 2013 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Modeling And Using Context

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Author : Boicho Kokinov
language : en
Publisher: Springer
Release Date : 2007-08-28

Modeling And Using Context written by Boicho Kokinov and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-28 with Computers categories.

Here are the refereed proceedings of the 6th International and Interdisciplinary Conference on Modeling and Using Context. The 42 papers deal with the interdisciplinary topic of modeling and using context from various perspectives, including computer science, artificial intelligence, cognitive science, linguistics, organizational science, philosophy, and psychology. In addition, readers discover applications in areas such as medicine and law.

Stream Processing With Apache Spark

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Author : Gerard Maas
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2019-06-05

Stream Processing With Apache Spark written by Gerard Maas and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-05 with Computers categories.

Before you can build analytics tools to gain quick insights, you first need to know how to process data in real time. With this practical guide, developers familiar with Apache Spark will learn how to put this in-memory framework to use for streaming data. You’ll discover how Spark enables you to write streaming jobs in almost the same way you write batch jobs. Authors Gerard Maas and François Garillot help you explore the theoretical underpinnings of Apache Spark. This comprehensive guide features two sections that compare and contrast the streaming APIs Spark now supports: the original Spark Streaming library and the newer Structured Streaming API. Learn fundamental stream processing concepts and examine different streaming architectures Explore Structured Streaming through practical examples; learn different aspects of stream processing in detail Create and operate streaming jobs and applications with Spark Streaming; integrate Spark Streaming with other Spark APIs Learn advanced Spark Streaming techniques, including approximation algorithms and machine learning algorithms Compare Apache Spark to other stream processing projects, including Apache Storm, Apache Flink, and Apache Kafka Streams

Big Data In Complex Systems

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Author : Aboul Ella Hassanien
language : en
Publisher: Springer
Release Date : 2015-01-02

Big Data In Complex Systems written by Aboul Ella Hassanien and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-02 with Technology & Engineering categories.

This volume provides challenges and Opportunities with updated, in-depth material on the application of Big data to complex systems in order to find solutions for the challenges and problems facing big data sets applications. Much data today is not natively in structured format; for example, tweets and blogs are weakly structured pieces of text, while images and video are structured for storage and display, but not for semantic content and search. Therefore transforming such content into a structured format for later analysis is a major challenge. Data analysis, organization, retrieval, and modeling are other foundational challenges treated in this book. The material of this book will be useful for researchers and practitioners in the field of big data as well as advanced undergraduate and graduate students. Each of the 17 chapters in the book opens with a chapter abstract and key terms list. The chapters are organized along the lines of problem description, related works, and analysis of the results and comparisons are provided whenever feasible.

Machine Learning And Knowledge Discovery In Databases Research Track

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Author : Nuria Oliver
language : en
Publisher: Springer Nature
Release Date : 2021-09-10

Machine Learning And Knowledge Discovery In Databases Research Track written by Nuria Oliver and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-10 with Computers categories.

The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic. The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions. The volumes are organized in topical sections as follows: Research Track: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and few-shot learning; learning algorithms and applications. Part II: Generative models; algorithms and learning theory; graphs and networks; interpretation, explainability, transparency, safety. Part III: Generative models; search and optimization; supervised learning; text mining and natural language processing; image processing, computer vision and visual analytics. Applied Data Science Track: Part IV: Anomaly detection and malware; spatio-temporal data; e-commerce and finance; healthcare and medical applications (including Covid); mobility and transportation. Part V: Automating machine learning, optimization, and feature engineering; machine learning based simulations and knowledge discovery; recommender systems and behavior modeling; natural language processing; remote sensing, image and video processing; social media.

Machine Learning For Data Science Handbook

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Author : Lior Rokach
language : en
Publisher: Springer Nature
Release Date : 2023-08-17

Machine Learning For Data Science Handbook written by Lior Rokach and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-17 with Computers categories.

This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries.

Machine Learning Under Resource Constraints Fundamentals

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Author : Katharina Morik
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2022-12-31

Machine Learning Under Resource Constraints Fundamentals written by Katharina Morik and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-31 with Science categories.

Machine Learning under Resource Constraints addresses novel machine learning algorithms that are challenged by high-throughput data, by high dimensions, or by complex structures of the data in three volumes. Resource constraints are given by the relation between the demands for processing the data and the capacity of the computing machinery. The resources are runtime, memory, communication, and energy. Hence, modern computer architectures play a significant role. Novel machine learning algorithms are optimized with regard to minimal resource consumption. Moreover, learned predictions are executed on diverse architectures to save resources. It provides a comprehensive overview of the novel approaches to machine learning research that consider resource constraints, as well as the application of the described methods in various domains of science and engineering. Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to the different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Several machine learning methods are inspected with respect to their resource requirements and how to enhance their scalability on diverse computing architectures ranging from embedded systems to large computing clusters.

Advances In Cryptology Crypto 2014

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Author : Juan A. Garay
language : en
Publisher: Springer
Release Date : 2014-07-14

Advances In Cryptology Crypto 2014 written by Juan A. Garay and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-14 with Computers categories.

The two volume-set, LNCS 8616 and LNCS 8617, constitutes the refereed proceedings of the 34th Annual International Cryptology Conference, CRYPTO 2014, held in Santa Barbara, CA, USA, in August 2014. The 60 revised full papers presented in LNCS 8616 and LNCS 8617 were carefully reviewed and selected from 227 submissions. The papers are organized in topical sections on symmetric encryption and PRFs; formal methods; hash functions; groups and maps; lattices; asymmetric encryption and signatures; side channels and leakage resilience; obfuscation; FHE; quantum cryptography; foundations of hardness; number-theoretic hardness; information-theoretic security; key exchange and secure communication; zero knowledge; composable security; secure computation - foundations; secure computation - implementations.