NIST · ИТ · 58edb2f0ed89b32eb0aa
Dictionary Learning from Ambiguously Labeled Data
We propose a novel dictionary-based learning method for ambiguously labeled multiclass classification, where each training sample has multiple labels and only one of them is the correct label. The dictionary learning problem is solved using an iterative
NIST · ИТОфициальный источник · 2013-04-09
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"title_en": "Dictionary Learning from Ambiguously Labeled Data",
"designation": "",
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"date": "2013-04-09",
"date_original": "April 9, 2013",
"url": "https://www.nist.gov/publications/dictionary-learning-ambiguously-labeled-data",
"source": "NIST Publications",
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"authors_en": "P J. Phillips , Yi-Chen Chen, Vishal M. Patel, Jaishanker K. Pillai, Rama Chellappa",
"abstract_excerpt_en": "We propose a novel dictionary-based learning method for ambiguously labeled multiclass classification, where each training sample has multiple labels and only one of them is the correct label. The dictionary learning problem is solved using an iterative",
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"title_en": "Dictionary Learning from Ambiguously Labeled Data",
"designation": "",
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"date": "2013-04-09",
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"url": "https://www.nist.gov/publications/dictionary-learning-ambiguously-labeled-data",
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"authors_en": "P J. Phillips , Yi-Chen Chen, Vishal M. Patel, Jaishanker K. Pillai, Rama Chellappa",
"abstract_excerpt_en": "We propose a novel dictionary-based learning method for ambiguously labeled multiclass classification, where each training sample has multiple labels and only one of them is the correct label. The dictionary learning problem is solved using an iterative"
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