Ergebnisse für: robust data mining
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Data uncertainty is a concept closely related with most real life applications that involve data collection and interpretation. Examples can be found in data acquired with biomedical instruments or other experimental techniques. Integration of robust optimization in the existing data mining techniqu...
Data uncertainty is a concept closely related with most real life applications that involve data collection and interpretation. Examples can be found in data acquired with biomedical instruments or other experimental techniques. Integration of robust optimization in the existing data mining techniqu...
The collection and analysis of data play an important role in many fields of science and technology, such as computational biology, quantitative finance, information engineering, machine learning, neuroscience, medicine, and the social sciences. Especially in the era of big data, researchers can e...
This contributed volume collects research papers, presented at the CIRP Sponsored Conference Robust Manufacturing Control: Innovative and Interdisciplinary Approaches for Global Networks (RoMaC 2012, Jacobs University, Bremen, Germany, June 18th-20th 2012). These research papers present the latest d...
This volume on statistical methods for data analysis and decision sciences showcases the interplay between statistics and data science, reflecting a broad spectrum of data-driven challenges, innovative approaches, methodological developments and applications. It gathers peer-reviewed short papers pr...
This book constitutes the refereed proceedings of the 11th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2015, held in Hamburg, Germany in July 2015. The 41 full papers presented were carefully reviewed and selected from 123 submissions. The topics range f...
This book constitutes the refereed proceedings of the 11th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2015, held in Hamburg, Germany in July 2015. The 41 full papers presented were carefully reviewed and selected from 123 submissions. The topics range f...
The collection and analysis of data play an important role in many fields of science and technology, such as computational biology, quantitative finance, information engineering, machine learning, neuroscience, medicine, and the social sciences. Especially in the era of big data, researchers can e...
The collection and analysis of data play an important role in many fields of science and technology, such as computational biology, quantitative finance, information engineering, machine learning, neuroscience, medicine, and the social sciences. Especially in the era of big data, researchers can e...
Incomplete big data are frequently encountered in many industrial applications, such as recommender systems, the Internet of Things, intelligent transportation, cloud computing, and so on. It is of great significance to analyze them for mining rich and valuable knowledge and patterns. Latent feature...
Incomplete big data are frequently encountered in many industrial applications, such as recommender systems, the Internet of Things, intelligent transportation, cloud computing, and so on. It is of great significance to analyze them for mining rich and valuable knowledge and patterns. Latent feature...
This contributed volume collects research papers, presented at the CIRP Sponsored Conference Robust Manufacturing Control: Innovative and Interdisciplinary Approaches for Global Networks (RoMaC 2012, Jacobs University, Bremen, Germany, June 18th-20th 2012). These research papers present the latest d...
This contributed volume collects research papers, presented at the CIRP Sponsored Conference Robust Manufacturing Control: Innovative and Interdisciplinary Approaches for Global Networks (RoMaC 2012, Jacobs University, Bremen, Germany, June 18th-20th 2012). These research papers present the latest d...
Provides an applications-oriented introduction to robust regression and outlier detection, emphasising °high-breakdown° methods which can cope with a sizeable fraction of contamination. Its self-contained treatment allows readers to skip the mathematical material which is concentrated in a few sec...
WILEY-INTERSCIENCE PAPERBACK SERIES
The Wiley-Interscience Paperback Series consists of selectedbooks that have been made more accessible to consumers in an effortto increase global appeal and general circulation. With these newunabridged softcover volumes, Wiley hopes to extend the lives ofthese wo...
To tackle the challenges of the road estimation task, many works employ a fusion of multiple sources. By that, a commonly made assumption is that the sources always are equally reliable. However, this assumption is inappropriate since each source has certain advantages and drawbacks depending on the...
Discover key information buried in the noise of data by learning a variety of anomaly detection techniques and using the Python programming language to build a robust service for anomaly detection against a variety of data types. The book starts with an overview of what anomalies and outliers are an...
Discover key information buried in the noise of data by learning a variety of anomaly detection techniques and using the Python programming language to build a robust service for anomaly detection against a variety of data types. The book starts with an overview of what anomalies and outliers are an...
To tackle the challenges of the road estimation task, many works employ a fusion of multiple sources. By that, a commonly made assumption is that the sources always are equally reliable. However, this assumption is inappropriate since each source has certain advantages and drawbacks depending on the...
This volume on statistical methods for data analysis and decision sciences showcases the interplay between statistics and data science, reflecting a broad spectrum of data-driven challenges, innovative approaches, methodological developments and applications. It gathers peer-reviewed short papers pr...