Proceedings of Second International Conference on Computing, Communications, and Cyber-Security PDF Download

Author: Pradeep Kumar Singh
Publisher: Springer Nature
ISBN: 9811607338
Category : Technology & Engineering
Languages : en
Pages : 1027

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Book Description
This book features selected research papers presented at the Second International Conference on Computing, Communications, and Cyber-Security (IC4S 2020), organized in Krishna Engineering College (KEC), Ghaziabad, India, along with Academic Associates; Southern Federal University, Russia; IAC Educational, India; and ITS Mohan Nagar, Ghaziabad, India during 3–4 October 2020. It includes innovative work from researchers, leading innovators, and professionals in the area of communication and network technologies, advanced computing technologies, data analytics and intelligent learning, the latest electrical and electronics trends, and security and privacy issues.

Author: Jinho Kim
Publisher: Springer
ISBN: 3319575295
Category : Computers
Languages : en
Pages : 876

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Book Description
This two-volume set, LNAI 10234 and 10235, constitutes the thoroughly refereed proceedings of the 21st Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017. The 129 full papers were carefully reviewed and selected from 458 submissions. They are organized in topical sections named: classification and deep learning; social network and graph mining; privacy-preserving mining and security/risk applications; spatio-temporal and sequential data mining; clustering and anomaly detection; recommender system; feature selection; text and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms; behavioral data mining; graph clustering and community detection; dimensionality reduction.

Author: Suparna Bhattacharya
Publisher: CRC Press
ISBN: 1351682334
Category : Computers
Languages : en
Pages : 355

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Book Description
Efficiency is a crucial concern across computing systems, from the edge to the cloud. Paradoxically, even as the latencies of bottleneck components such as storage and networks have dropped by up to four orders of magnitude, software path lengths have progressively increased due to overhead from the very frameworks that have revolutionized the pace of information technology. Such overhead can be severe enough to overshadow the benefits from switching to new technologies like persistent memory and low latency interconnects. Resource Proportional Software Design for Emerging Systems introduces resource proportional design (RPD) as a principled approach to software component and system development that counters the overhead of deeply layered code without removing flexibility or ease of development. RPD makes resource consumption proportional to situational utility by adapting to diverse emerging needs and technology systems evolution. Highlights: Analysis of run-time bloat in deep software stacks, an under-explored source of power-performance wastage in IT systems Qualitative and quantitative treatment of key dimensions of resource proportionality Code features: Unify and broaden supported but optional features without losing efficiency Technology and systems evolution: Design software to adapt with changing trade-offs as technology evolves Data processing: Design systems to predict which subsets of data processed by an (analytics or ML) application are likely to be useful System wide trade-offs: Address interacting local and global considerations throughout software stacks and hardware including cross-layer co-design involving code, data and systems dimensions, and non-functional requirements such as security and fault tolerance Written from a systems perspective to explore RPD principles, best practices, models and tools in the context of emerging technologies and applications This book is primarily geared towards practitioners with some advanced topics for researchers. The principles shared in the book are expected to be useful for programmers, engineers and researchers interested in ensuring software and systems are optimized for existing and next generation technologies. The authors are from both industry (Bhattacharya and Voigt) and academic (Gopinath) backgrounds.

Author: Padmanabhan Krishnan
Publisher: Springer
ISBN: 331950472X
Category : Computers
Languages : en
Pages : 247

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Book Description
This book constitutes the proceedings of the 13th International Conference on Distributed Computing and Internet Technology, ICDCIT 2017, held in Bhubaneswar, India, in January 2017. The 17 full papers and 3 poster papers presented together with 6 abstracts of invited talks were carefully reviewed and selected from 208 submissions (118 abstract and 90 full paper submissions). The ICDCIT conference focusses on mobile computing; analytics; distributed computing; virtual machines; access control; and security and privacy.

Author: Frank Hutter
Publisher: Springer
ISBN: 3030053180
Category : Computers
Languages : en
Pages : 223

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Book Description
This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.

Author: John Anderson
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Author: Osval Antonio Montesinos López
Publisher: Springer Nature
ISBN: 3030890104
Category : Technology & Engineering
Languages : en
Pages : 707

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Book Description
This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.

Author: Stephen Boyd
Publisher: Now Publishers Inc
ISBN: 160198460X
Category : Computers
Languages : en
Pages : 138

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Book Description
Surveys the theory and history of the alternating direction method of multipliers, and discusses its applications to a wide variety of statistical and machine learning problems of recent interest, including the lasso, sparse logistic regression, basis pursuit, covariance selection, support vector machines, and many others.

Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1668462923
Category : Computers
Languages : en
Pages : 1516

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Book Description
Machine learning continues to have myriad applications across industries and fields. To ensure this technology is utilized appropriately and to its full potential, organizations must better understand exactly how and where it can be adapted. Further study on the applications of machine learning is required to discover its best practices, challenges, and strategies. The Research Anthology on Machine Learning Techniques, Methods, and Applications provides a thorough consideration of the innovative and emerging research within the area of machine learning. The book discusses how the technology has been used in the past as well as potential ways it can be used in the future to ensure industries continue to develop and grow. Covering a range of topics such as artificial intelligence, deep learning, cybersecurity, and robotics, this major reference work is ideal for computer scientists, managers, researchers, scholars, practitioners, academicians, instructors, and students.

Author: Dirk P. Kroese
Publisher: CRC Press
ISBN: 1000730778
Category : Business & Economics
Languages : en
Pages : 538

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Book Description
Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code