Descripción:
Now Publishers Inc, 2021. Paperback. New. 188 pages. 9.21x6.14x0.40 inches.
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Minimum-Distortion Embedding Tapa blanda - 2021
de Akshay Agrawal; Alnur Ali; Stephen Boyd
Detalles
- Título Minimum-Distortion Embedding
- Autor Akshay Agrawal; Alnur Ali; Stephen Boyd
- Encuadernación Tapa blanda
- Páginas 188
- Volúmenes 1
- Idioma ENG
- Editorial Now Publishers
- Fecha de publicación 2021-09-08
- ISBN 9781680838886 / 1680838881
- Peso 0.6 libras (0.27 kg)
- Dimensiones 9.21 x 6.14 x 0.4 pulgadas (23.39 x 15.60 x 1.02 cm)
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Minimum-Distortion Embedding (Foundations and Trends® in Machine Learning)
de Agrawal, Akshay/ Ali, Alnur/ Boyd, Stephen
- Nuevo
- Tapa blanda
- Estado
- Nuevo
- Encuadernación
- Paperback
- ISBN 10 / ISBN 13
- 9781680838886 / 1680838881
- Cantidad disponible
- 2
- Librería
-
Exeter, Devon, United Kingdom
- Precio
-
EUR 94.76EUR 11.90 enviando a USA
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Precio
EUR 94.76
EUR 11.90
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Minimum-Distortion Embedding
de Akshay Agrawal
- Nuevo
- Estado
- Nuevo
- ISBN 10 / ISBN 13
- 9781680838886 / 1680838881
- Cantidad disponible
- 10
- Librería
-
Southport, Merseyside, United Kingdom
- Precio
-
EUR 120.30EUR 11.84 enviando a USA
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Descripción:
New. Embeddings provide concrete numerical representations of otherwise abstract items, for use in downstream tasks. For example, a biologist might look for subfamilies of related cells by clustering embedding vectors associated with individual cells, while a machine learning practitioner might use vector representations of words as features for a classification task. In this monograph the authors present a general framework for faithful embedding called minimum-distortion embedding (MDE) that generalizes the common cases in which similarities between items are described by weights or distances. The MDE framework is simple but general. It includes a wide variety of specific embedding methods, including spectral embedding, principal component analysis, multidimensional scaling, Euclidean distance problems, etc.The authors provide a detailed description of minimum-distortion embedding problem and describe the theory behind creating solutions to all aspects. They also give describe in detail algorithms…
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EUR 120.30
EUR 11.84
enviando a USA
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Minimum-Distortion Embedding (Foundations and Trends(r) in Machine Learning)
de Agrawal, Akshay
- Usado
- Bien
- Tapa blanda
- Estado
- Usado - Bien
- Encuadernación
- Paperback
- ISBN 10 / ISBN 13
- 9781680838886 / 1680838881
- Cantidad disponible
- 1
- Librería
-
Newport Coast, California, United States
- Precio
-
EUR 151.89Envío gratuito a USA
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Descripción:
paperback. Good. Access codes and supplements are not guaranteed with used items. May be an ex-library book.
Precio
EUR 151.89
Envío gratuito a USA
Minimum-Distortion Embedding (Foundations and Trends(r) in Machine Learning)
de Agrawal, Akshay; Ali, Alnur; Boyd, Stephen
- Nuevo
- Tapa blanda
- Estado
- Nuevo
- Encuadernación
- Paperback
- ISBN 10 / ISBN 13
- 9781680838886 / 1680838881
- Cantidad disponible
- 2
- Librería
-
Kraków, Poland
- Precio
-
EUR 58.32EUR 15.16 enviando a USA
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Descripción:
Now Publishers, 2021 8vo (23.5 cm). X, 174 pp. Laminated wrappers. "Embeddings provide concrete numerical representations of otherwise abstract items, for use in downstream tasks. For example, a biologist might look for subfamilies of related cells by clustering embedding vectors associated with individual cells, while a machine learning practitioner might use vector representations of words as features for a classification task. In this monograph the authors present a general framework for faithful embedding called minimum-distortion embedding (MDE) that generalizes the common cases in which similarities between items are described by weights or distances. The MDE framework is simple but general. It includes a wide variety of specific embedding methods, including spectral embedding, principal component analysis, multidimensional scaling, Euclidean distance problems, etc. The authors provide a detailed description of minimum-distortion embedding problem and describe the theory behind creating…
Leer más Precio
EUR 58.32
EUR 15.16
enviando a USA