Titlebook: Big Data Optimization: Recent Developments and Challenges; Ali Emrouznejad Book 2016 Springer International Publishing Switzerland 2016 Bi

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Introduction to Clinical Informaticsof tens of million data points. Mathematically based models for their improvement—due to noise, camera shake, physical and technical limitations, etc.—are moreover often highly non-smooth and increasingly often non-convex. This creates significant optimisation challenges for the application of the m

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Arthur N. Wiens,Angelique G. Tindalls is getting large scale, never ending, and ever changing, arriving in batches at irregular time intervals. Examples of these are social and business data. Linking and analyzing of this potentially connected data is of high and valuable interest. In this context, it will be important to investigate

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Introduction to Clinical Psychologys, and Principal component analysis. The related area of Topological Data Analysis (TDA) has been developing in the last decade. The idea is to extract robust topological features from data and use these summaries for modeling the data. A topological summary generates a coordinate-free, deformation

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Robert L. Hale,Elizabeth A. Greenasingly digital and interconnected world requires both new data analysis algorithms and a new class of systems to handle the dramatic data growth, the demand to integrate structured and unstructured data analytics, and the increasing computing needs of massive-scale analytics. As a result, massive-s

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Arthur N. Wiens,Angelique G. Tindalle interpretation also grows. To this, as decision makers require the timely arrival of information, the need for high performance interpretation of measurement data also grows. Big Data optimization techniques can enable designers and engineers to realize large scale monitoring systems in real life,

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