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Stefan Riezler is a full professor in the Department of Computational Linguistics at Heidelberg University, Germany since 2010, and also co-opted in Informatics at the Department of Mathematics and Computer Science. He received his Ph.D. (with distinction) in Computational Linguistics from the University of Tübingen in 1998, conducted post-doctoral work at Brown University in 1999, and spent a decade in industry research (Xerox PARC, Google Research). His research focus is on inter-active machine learning for natural language processing problems especially for the application areas of cross-lingual information retrieval and statistical machine trans-lation. He is engaged as an editorial board member of the main journals of the field-Computational Linguistics and Transactions of the Association for Computational Linguistics-and is a regular member of the program committee of various natural language processing and machine learning conferences.He has published more than 100 journal and conference papers in these areas. He also conducts interdisciplinary research as member of the Interdisciplinary Center for Scientific Computing (IWR), for example, on the topic of early prediction of sepsis using machine learning and natural language processing techniques.
Michael Hagmann is a graduate research assistant in the Department of Computational Linguistics at Heidelberg University, Germany, since 2019. He received an M.Sc. in Statistics (with distinction) from the University of Vienna, Austria in 2016, and a Ph.D. in Computational Linguistics from Heidelberg University in 2023. He received an award for the best Master's thesis in Applied Statistics from the Austrian Statistical Society. He has worked as a medical statistician at the medical faculty of Heidelberg University in Mannheim, Germany and in the section for Medical Statistics at the Medical University of Vienna, Austria. His research focus is on statistical methods for data science and, recently, NLP. He has published more than 50 papers in journals for medical research and mathematical statistics.
Preface.- Acknowledgments.- Introduction.- Validity.- Reliability.- Significance.- Worked-Through Example: Analyzing Inferential Reproducibility.- Bibliography.
Erscheinungsjahr: | 2024 |
---|---|
Genre: | Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
Reihe: | Synthesis Lectures on Human Language Technologies |
Inhalt: |
xvii
168 S. 9 s/w Illustr. 61 farbige Illustr. 168 p. 70 illus. 61 illus. in color. |
ISBN-13: | 9783031570643 |
ISBN-10: | 3031570642 |
Sprache: | Englisch |
Ausstattung / Beilage: | HC runder Rücken kaschiert |
Einband: | Gebunden |
Autor: |
Hagmann, Michael
Riezler, Stefan |
Auflage: | Second Edition 2024 |
Hersteller: |
Springer Nature Switzerland
Springer International Publishing Synthesis Lectures on Human Language Technologies |
Maße: | 246 x 173 x 16 mm |
Von/Mit: | Michael Hagmann (u. a.) |
Erscheinungsdatum: | 10.06.2024 |
Gewicht: | 0,502 kg |
Stefan Riezler is a full professor in the Department of Computational Linguistics at Heidelberg University, Germany since 2010, and also co-opted in Informatics at the Department of Mathematics and Computer Science. He received his Ph.D. (with distinction) in Computational Linguistics from the University of Tübingen in 1998, conducted post-doctoral work at Brown University in 1999, and spent a decade in industry research (Xerox PARC, Google Research). His research focus is on inter-active machine learning for natural language processing problems especially for the application areas of cross-lingual information retrieval and statistical machine trans-lation. He is engaged as an editorial board member of the main journals of the field-Computational Linguistics and Transactions of the Association for Computational Linguistics-and is a regular member of the program committee of various natural language processing and machine learning conferences.He has published more than 100 journal and conference papers in these areas. He also conducts interdisciplinary research as member of the Interdisciplinary Center for Scientific Computing (IWR), for example, on the topic of early prediction of sepsis using machine learning and natural language processing techniques.
Michael Hagmann is a graduate research assistant in the Department of Computational Linguistics at Heidelberg University, Germany, since 2019. He received an M.Sc. in Statistics (with distinction) from the University of Vienna, Austria in 2016, and a Ph.D. in Computational Linguistics from Heidelberg University in 2023. He received an award for the best Master's thesis in Applied Statistics from the Austrian Statistical Society. He has worked as a medical statistician at the medical faculty of Heidelberg University in Mannheim, Germany and in the section for Medical Statistics at the Medical University of Vienna, Austria. His research focus is on statistical methods for data science and, recently, NLP. He has published more than 50 papers in journals for medical research and mathematical statistics.
Preface.- Acknowledgments.- Introduction.- Validity.- Reliability.- Significance.- Worked-Through Example: Analyzing Inferential Reproducibility.- Bibliography.
Erscheinungsjahr: | 2024 |
---|---|
Genre: | Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
Reihe: | Synthesis Lectures on Human Language Technologies |
Inhalt: |
xvii
168 S. 9 s/w Illustr. 61 farbige Illustr. 168 p. 70 illus. 61 illus. in color. |
ISBN-13: | 9783031570643 |
ISBN-10: | 3031570642 |
Sprache: | Englisch |
Ausstattung / Beilage: | HC runder Rücken kaschiert |
Einband: | Gebunden |
Autor: |
Hagmann, Michael
Riezler, Stefan |
Auflage: | Second Edition 2024 |
Hersteller: |
Springer Nature Switzerland
Springer International Publishing Synthesis Lectures on Human Language Technologies |
Maße: | 246 x 173 x 16 mm |
Von/Mit: | Michael Hagmann (u. a.) |
Erscheinungsdatum: | 10.06.2024 |
Gewicht: | 0,502 kg |