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Probabilistic Data Structures and Algorithms for Big Data Applications

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Probabilistic Data Structures

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Probabilistic Data Structures for Blockchain-Based Internet of Things Applications

This book covers theory and practical knowledge of Probabilistic data structures (PDS) and Blockchain (BC) concepts. It introduces the;

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Query Processing on Probabilistic Data

Probabilistic data is motivated by the need to model uncertainty in large databases. Over the last twenty years or so, both the Database;

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Data Structures and Algorithms Using C#

C# programmers: no more translating data structures from C++ or Java to use in your programs! Mike McMillan provides a tutorial on how to;

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Data Structures and Algorithms Using C#

C# programmers: no more translating data structures from C++ or Java to use in your programs! Mike McMillan provides a tutorial on how to;

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Hydraulic Structures

Hydraulic Structures: Probabilistic Approaches to Maintenance is an introduction to the field of probability theory and its applications;

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Reliability of Geotechnical Structures in ISO2394

The latest 4th edition of the international standard on the principles of reliability for load bearing structures (ISO2394:2015) includes a;

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Probabilistic Databases

integration, and financial risk assessment produce large volumes of uncertain data, which are best modeled and processed by a probabilistic database;

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Probabilistic Databases

integration, and financial risk assessment produce large volumes of uncertain data, which are best modeled and processed by a probabilistic database;

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Data Structures and Algorithms Using Visual Basic.NET

This is the first Visual Basic.NET book to provide a comprehensive discussion of the major data structures and algorithms. Here, instead;

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Average Case Analysis of Algorithms on Sequences

biology, data compression, security, and pattern matching. Includes chapters on algorithms and data structures on words, probabilistic and;

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Computational Mechanics of Composite Materials

and mechanics with the probabilistic approach to experimental data in meeting the practical needs of engineers. Features;

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Probabilistic Transmission System Planning

, which discuss the concepts, models, methods and data in probabilistic transmission planning. The second part, Chapters 8 to 11, addresses four;

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Analyzing Data Through Probabilistic Modeling in Statistics

research on the impact of such probabilistic modeling with other approaches. Analyzing Data Through Probabilistic Modeling in Statistics is an;

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Practical Probabilistic Programming

the future! Probabilistic programming is a programming paradigm in which code models are used to draw probabilistic inferences from data. By;

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Probabilistic Risk and Hazard Assessment: Proceedings of the Conference, Newcastle, Nsw, Australia, 22-23 September 1993

Highlights the multi-disciplinary nature of probabilistic risk and hazard assessment procedures. Topics covered include: Hazard scenario;

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Algorithms and Data Structures

randomized algorithm. Data structures are discussed to the extent needed for the implementation of the algorithms. The specific algorithms examined;

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Linguistic Structure Prediction

related topics in probabilistic inference, optimization, and experimental methodology. Table of Contents: Representations and Linguistic Data;

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14th International Probabilistic Workshop

This book presents the proceedings of the 14th International Probabilistic Workshop that was held in Ghent, Belgium in December 2016;

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18th International Probabilistic Workshop

This volume presents the proceedings of the 18th International Probabilistic Workshop (IPW), which was held in Guimaraes, Portugal in May;

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Data Fusion for WSN Using Probabilistic Method and Particle Filter

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Stochastic Causality

analysis of probabilistic data; others address causal issues in physics, with an emphasis on physical processes that are also probabilistic-i.e;

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Probabilistic Structural Mechanics Handbook

The need for a comprehensive book on probabilistic structural mechanics that brings together the many analytical and computational methods;

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Random Signals

filtering; and statistical estimation - the measurement and analysis of random data to determine the structure and parameter values of probabilistic;

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Probabilistic Approaches to Recommendations

Next, we introduce and discuss probabilistic approaches for modeling preference data. We focus our attention on methods based on latent factors;

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Probabilistic Approaches to Recommendations

Next, we introduce and discuss probabilistic approaches for modeling preference data. We focus our attention on methods based on latent factors;

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