Alexander Gammerman - Böcker
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7 produkter
7 produkter
1 792 kr
Skickas inom 10-15 vardagar
This book is about conformal prediction, an approach to prediction that originated in machine learning in the late 1990s.
634 kr
Skickas inom 5-8 vardagar
1 792 kr
Skickas inom 10-15 vardagar
This book is about conformal prediction, an approach to prediction that originated in machine learning in the late 1990s.
Del 9047 - Lecture Notes in Computer Science
Statistical Learning and Data Sciences
Third International Symposium, SLDS 2015, Egham, UK, April 20-23, 2015, Proceedings
Häftad, Engelska, 2015
553 kr
Skickas inom 10-15 vardagar
This book constitutes the refereed proceedings of the Third International Symposium on Statistical Learning and Data Sciences, SLDS 2015, held in Egham, Surrey, UK, April 2015.
1 067 kr
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This book brings together historical notes, reviews of research developments, fresh ideas on how to make VC (Vapnik–Chervonenkis) guarantees tighter, and new technical contributions in the areas of machine learning, statistical inference, classification, algorithmic statistics, and pattern recognition. The contributors are leading scientists in domains such as statistics, mathematics, and theoretical computer science, and the book will be of interest to researchers and graduate students in these domains.
Del 9653 - Lecture Notes in Computer Science
Conformal and Probabilistic Prediction with Applications
5th International Symposium, COPA 2016, Madrid, Spain, April 20-22, 2016, Proceedings
Häftad, Engelska, 2016
553 kr
Skickas inom 10-15 vardagar
This book constitutes the refereed proceedings of the 5th InternationalSymposium on Conformal and Probabilistic Prediction with Applications, COPA2016, held in Madrid, Spain, in April 2016.The 14 revised fullpapers presented together with 1 invited paper were carefully reviewed andselected from 23 submissions and cover topics on theory of conformal prediction; applicationsof conformal prediction; and machine learning.
1 067 kr
Skickas inom 10-15 vardagar
This book brings together historical notes, reviews of research developments, fresh ideas on how to make VC (Vapnik–Chervonenkis) guarantees tighter, and new technical contributions in the areas of machine learning, statistical inference, classification, algorithmic statistics, and pattern recognition.