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Titlebook: Machine Learning for Adaptive Many-Core Machines - A Practical Approach; Noel Lopes,Bernardete Ribeiro Book 2015 Springer International Pu

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發(fā)表于 2025-3-21 19:50:20 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Machine Learning for Adaptive Many-Core Machines - A Practical Approach
編輯Noel Lopes,Bernardete Ribeiro
視頻videohttp://file.papertrans.cn/621/620581/620581.mp4
概述Recent research in machine learning for adaptive many-core machines.Presents a practical approach.Written by experts in the field
叢書(shū)名稱Studies in Big Data
圖書(shū)封面Titlebook: Machine Learning for Adaptive Many-Core Machines - A Practical Approach; Noel Lopes,Bernardete Ribeiro Book 2015 Springer International Pu
描述.The overwhelming data produced everyday and the increasing performance and cost requirements of applications?are transversal to a wide range of activities in society, from science to industry. In particular, the magnitude and complexity of the tasks that Machine Learning (ML) algorithms have to solve are driving the need to devise adaptive many-core machines that scale well with the volume of data, or in other words, can handle Big Data..This book gives a concise view on how to extend the applicability of well-known ML algorithms in Graphics Processing Unit (GPU) with data scalability in mind. It presents a series of new techniques to enhance, scale and distribute data in a Big Learning framework. It is not intended to be a comprehensive survey of the state of the art of the whole field of machine learning for Big Data. Its purpose is less ambitious and more practical: to explain and illustrate existing and novel GPU-based ML algorithms, not viewed as a universal solution for the Big Data challenges but rather as part of the answer, which may require the use of different strategies coupled together..
出版日期Book 2015
關(guān)鍵詞Adaptive Many-Core Machines; Big Data; Machine Learning
版次1
doihttps://doi.org/10.1007/978-3-319-06938-8
isbn_softcover978-3-319-38096-4
isbn_ebook978-3-319-06938-8Series ISSN 2197-6503 Series E-ISSN 2197-6511
issn_series 2197-6503
copyrightSpringer International Publishing Switzerland 2015
The information of publication is updating

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Noel Lopes,Bernardete Ribeirobility in two of the world‘s most widely spoken languages.Us? This volume contributes to the research in two different research areas: lexical availability studies and vocabulary research in second or foreign languages. Lexical availability is defined as the words that immediately come to mind as a
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amiliarity (Hernández Mu?oz N, Izura C, Ellis AW, Eur J Cogn Psychol 18:734–755, 2006). The influence of these factors might change in second languages (L2) due to variations in age of learning, motivation, learning processes and experience of linguistic material amongst other factors. The aim of th
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Noel Lopes,Bernardete Ribeiro most studies, however, the results of one parser are compared to those of relatively “dumb” window-based approaches only. To date, the impact of the parser used and its parsing scheme has not been studied systematically to the best of our knowledge. This chapter evaluates a total of 8 parsers on 2
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Noel Lopes,Bernardete Ribeiroity to the medium of writing. It was important to assess the extent to which vocabulary diversity as measured by D, and word rarity continued to be valid developmental measures in older children producing samples of writing. That is to say, do these measures continue to improve in line with increasi
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Noel Lopes,Bernardete Ribeiroity to the medium of writing. It was important to assess the extent to which vocabulary diversity as measured by D, and word rarity continued to be valid developmental measures in older children producing samples of writing. That is to say, do these measures continue to improve in line with increasi
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Noel Lopes,Bernardete Ribeiroity to the medium of writing. It was important to assess the extent to which vocabulary diversity as measured by D, and word rarity continued to be valid developmental measures in older children producing samples of writing. That is to say, do these measures continue to improve in line with increasi
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