eBook, PDF

Advances in Machine Learning and Data Mining for Astronomy (eBook, PDF)

Beschreibung

Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines

Technische Details

• Geräte: PC
• mit Kopierschutz
• Größe: 18.2MB

Barrierefreiheit

• Text-to-Speech
• E-Mail des Verlags für Barrierefreiheitsfragen: [e-mail]
• Seitennummerierung folgt dem gedruckten Werk
• Kurze Alternativtexte für nicht-textuelle Inhalte vorhanden
• Navigierbares Inhaltsverzeichnis für direkten Zugriff auf Text und Medien

Autor

Michael J. Way, PhD, is a research scientist at the NASA Goddard Institute for Space Studies in New York and the NASA Ames Research Center in California. He is also an adjunct professor in the Department of Physics and Astronomy at Hunter College. His research focuses on understanding the multiscale structure of our universe, modeling the atmospheres of exoplanets, and applying kernel methods to new areas in astronomy. Jeffrey D. Scargle, PhD, is an astrophysicist in the Space Science and Astrobiology Division of the NASA Ames Research Center. His main interests encompass the variability of astronomical objects, including the Sun, sources in the Galaxy, and active galactic nuclei; cosmology; plasma astrophysics; planetary detection; and data analysis and statistical methods. Kamal M. Ali, PhD, is a research scientist in machine learning and data mining. He has a consulting practice and is cofounder of the start-up Metric Avenue. He has carried out research at IBM Almaden, Stanford University, Vividence, Yahoo, and TiVo, where he worked on the Tivo Collaborative Filtering Engine. His current research focuses on combining machine learning in conditional random fields with linguistically rich features to make machines better at reading web pages. Ashok N. Srivastava, PhD, is the principal scientist for Data Mining and Systems Health Management and leader of the Intelligent Data Understanding group at NASA Ames Research Center. His research includes the development of data mining algorithms for anomaly detection in massive data streams, kernel methods in machine learning, and text mining algorithms.

Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 744
• Erscheinungstermin: 29. März 2012
• Englisch
• ISBN-13: 9781439841747
• Artikelnr.: 38303220