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pro vyhledávání: '"Huang, Boshuang"'
Autor:
Markov, Igor L., Wang, Hanson, Kasturi, Nitya, Singh, Shaun, Yuen, Sze Wai, Garrard, Mia, Tran, Sarah, Huang, Yin, Wang, Zehui, Glotov, Igor, Gupta, Tanvi, Huang, Boshuang, Chen, Peng, Xie, Xiaowen, Belkin, Michael, Uryasev, Sal, Howie, Sam, Bakshy, Eytan, Zhou, Norm
Modern software systems and products increasingly rely on machine learning models to make data-driven decisions based on interactions with users, infrastructure and other systems. For broader adoption, this practice must (i) accommodate product engin
Externí odkaz:
http://arxiv.org/abs/2110.07554
We study online active learning for classifying streaming instances within the framework of statistical learning theory. At each time, the learner either queries the label of the current instance or predicts the label based on past seen examples. The
Externí odkaz:
http://arxiv.org/abs/1904.09056
An active inference problem of detecting anomalies among heterogeneous processes is considered. At each time, a subset of processes can be probed. The objective is to design a sequential probing strategy that dynamically determines which processes to
Externí odkaz:
http://arxiv.org/abs/1704.00766
Autor:
Markov, Igor L., Wang, Hanson, Kasturi, Nitya, Singh, Shaun, Yuen, Sze Wai, Garrard, Mia, Tran, Sarah, Huang, Yin, Wang, Zehui, Glotov, Igor, Gupta, Tanvi, Huang, Boshuang, Chen, Peng, Xie, Xiaowen, Belkin, Michael, Uryasev, Sal, Howie, Sam, Bakshy, Eytan, Zhou, Norm
Publikováno v:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Modern software systems and products increasingly rely on machine learning models to make data-driven decisions based on interactions with users, infrastructure and other systems. For broader adoption, this practice must (i) accommodate product engin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4c264f8fb0d101232e5c800e91485926
https://doi.org/10.1145/3534678.3539059
https://doi.org/10.1145/3534678.3539059
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Akademický článek
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