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  3. Machine learning

Towards Integrative Machine Learning and Knowledge Extraction

- BIRS Workshop, Banff, AB, Canada, July 24-26, 2015, Revised Selected Papers
Engelsk Paperback

Towards Integrative Machine Learning and Knowledge Extraction

- BIRS Workshop, Banff, AB, Canada, July 24-26, 2015, Revised Selected Papers
Engelsk Paperback
Tjek vores konkurrenters priser

The BIRS Workshop "Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets" (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of "hot topics" toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain.

The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.

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Tjek vores konkurrenters priser
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Tjek vores konkurrenters priser

The BIRS Workshop "Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets" (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of "hot topics" toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain.

The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.

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Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 207
ISBN-13: 9783319697741
Indbinding: Paperback
Udgave:
ISBN-10: 3319697749
Kategori: Machine learning
Udg. Dato: 29 okt 2017
Længde: 0mm
Bredde: 155mm
Højde: 235mm
Forlag: Springer International Publishing AG
Oplagsdato: 29 okt 2017
Forfatter(e):
Forfatter(e)

Kategori Machine learning

ISBN-13 9783319697741

Sprog Engelsk

Indbinding Paperback

Sider 207

Udgave

Længde 0mm

Bredde 155mm

Højde 235mm

Udg. Dato 29 okt 2017

Oplagsdato 29 okt 2017

Forlag Springer International Publishing AG

Kategori sammenhænge