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Beyond Traditional Probabilistic Data Processing Techniques

interested in data processing under uncertainty, and an introduction to the latest trends and techniques in this area, suitable for graduate students.;

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Probabilistic Ranking Techniques in Relational Databases

formulations and processing techniques for ranking queries on uncertain data. The formulations are based on marriage of traditional ranking semantics;

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Probabilistic Ranking Techniques in Relational Databases

formulations and processing techniques for ranking queries on uncertain data. The formulations are based on marriage of traditional ranking semantics;

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Query Processing on Probabilistic Data

its relationship to probabilistic data. The monograph proceeds to discuss lifted probabilistic inference, a suite of techniques developed;

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Probabilistic Databases

. This book presents the state of the art in representation formalisms and query processing techniques for probabilistic data. It starts by;

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Probabilistic Databases

. This book presents the state of the art in representation formalisms and query processing techniques for probabilistic data. It starts by;

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Query Processing over Uncertain Databases

uncertain data, and finally discuss the advanced query processing techniques for various probabilistic queries in uncertain databases. The book;

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Query Processing over Uncertain Databases

uncertain data, and finally discuss the advanced query processing techniques for various probabilistic queries in uncertain databases. The book;

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Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas

% accurate. Measurement uncertainty is usually described using probabilistic techniques, while uncertainty in expert estimates is often described;

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Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas

% accurate. Measurement uncertainty is usually described using probabilistic techniques, while uncertainty in expert estimates is often described;

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Computational Learning And Probabilistic Reasoning

techniques for solving some important problems in machine intelligence and pattern recognition, namely probabilistic reasoning and computational;

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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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Principles of Database Query Processing for Advanced Applications

. Traditional techniques work well for databases with standard, single-site relational structures, but databases containing more complex and diverse;

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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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Intelligent Data Engineering and Automated Learning -- IDEAL 2013

, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, neural networks, probabilistic modelling;

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How Interval and Fuzzy Techniques Can Improve Teaching

This book explains how to teach better and presents the latest research on processing educational data and presents traditional statistical;

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Intelligent Data Engineering and Automated Learning - IDEAL 2016

; probabilistic modeling; particle swarm intelligence; big data analysis; applications in regression, classification, clustering, medical and biological;

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Intelligence Science and Big Data Engineering. Visual Data Engineering

including information theoretic and Bayesian approaches, probabilistic graphical models, big data analysis, neural networks and neuro-informatics;

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Robustness in Econometrics

This book presents recent research on robustness in econometrics. Robust data processing techniques - i.e., techniques that yield results;

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Image Processing and Data Analysis

Powerful techniques have been developed in recent years for the analysis of digital data, especially the manipulation of images. This book;

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Intelligent Data Engineering and Automated Learning IDEAL 2015

This book constitutes the refereed proceedings of the 16th International Conference on Intelligent Data Engineering and Automated;

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Intelligent Data Engineering and Automated Learning - IDEAL 2017

techniques to applications. In addition to various topics such as evolutionary algorithms, deep learning neural networks, probabilistic modelling;

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Intelligence Science and Big Data Engineering. Big Data and Machine Learning

including information theoretic and Bayesian approaches, probabilistic graphical models, big data analysis, neural networks and neuro-informatics;

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Large Scale and Big Data

Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques;

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Large Scale and Big Data

Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques;

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Scientific and Statistical Database Management

demonstration and poster papers were carefully reviewed and selected from numerous submissions. The topics covered are uncertain and probabilistic data;

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