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Towards increasing predictability of machine-learning research

<!--HTML--><p align="justify"> Dealing with system complexity is common problem for wide spectre of companies. It is always the case when people use machine learning for their needs. In Yandex as search engine company we are working with rapidly growing datasets, variety of dat...

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Detalles Bibliográficos
Autores principales: Vorozhtsov, Artem, Ustyuzhanin, Andrey
Lenguaje:eng
Publicado: 2013
Materias:
Acceso en línea:http://cds.cern.ch/record/1601031
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author Vorozhtsov, Artem
Ustyuzhanin, Andrey
author_facet Vorozhtsov, Artem
Ustyuzhanin, Andrey
author_sort Vorozhtsov, Artem
collection CERN
description <!--HTML--><p align="justify"> Dealing with system complexity is common problem for wide spectre of companies. It is always the case when people use machine learning for their needs. In Yandex as search engine company we are working with rapidly growing datasets, variety of data and different set of quality metrics. Usually research results in such environments are difficult to predict and tend to take unpredictable amount of time. </p> <p align="justify"> This talk describes several scenarios from Yandex everyday life that rely on machine learning techniques focusing on principles and instruments that help making research results more predictable both in terms of time required and quality of obtained results.</p>
id cern-1601031
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2013
record_format invenio
spelling cern-16010312022-11-02T22:30:06Zhttp://cds.cern.ch/record/1601031engVorozhtsov, ArtemUstyuzhanin, AndreyTowards increasing predictability of machine-learning researchTowards increasing predictability of machine-learning researchComputing Seminar<!--HTML--><p align="justify"> Dealing with system complexity is common problem for wide spectre of companies. It is always the case when people use machine learning for their needs. In Yandex as search engine company we are working with rapidly growing datasets, variety of data and different set of quality metrics. Usually research results in such environments are difficult to predict and tend to take unpredictable amount of time. </p> <p align="justify"> This talk describes several scenarios from Yandex everyday life that rely on machine learning techniques focusing on principles and instruments that help making research results more predictable both in terms of time required and quality of obtained results.</p>oai:cds.cern.ch:16010312013
spellingShingle Computing Seminar
Vorozhtsov, Artem
Ustyuzhanin, Andrey
Towards increasing predictability of machine-learning research
title Towards increasing predictability of machine-learning research
title_full Towards increasing predictability of machine-learning research
title_fullStr Towards increasing predictability of machine-learning research
title_full_unstemmed Towards increasing predictability of machine-learning research
title_short Towards increasing predictability of machine-learning research
title_sort towards increasing predictability of machine-learning research
topic Computing Seminar
url http://cds.cern.ch/record/1601031
work_keys_str_mv AT vorozhtsovartem towardsincreasingpredictabilityofmachinelearningresearch
AT ustyuzhaninandrey towardsincreasingpredictabilityofmachinelearningresearch