"Co-Trained" meaning in English

See Co-Trained in All languages combined, or Wiktionary

Adjective

IPA: /ˌkoʊˈtɹeɪnd/
Etymology: From co- + trained. Etymology templates: {{af|en|co-|trained}} co- + trained Head templates: {{en-adj|-}} Co-Trained (not comparable)
  1. (artificial intelligence, machine learning) Trained jointly or simultaneously alongside another model, classifier, or network component, typically processing distinct feature sets, data views, or modalities. Tags: not-comparable Related terms: co-train, co-training
    Sense id: en-Co-Trained-en-adj-CLY-rqL6 Categories (other): Artificial intelligence, Machine learning
  2. (artificial intelligence, machine learning, by extension) Mutually optimized or enhanced through a collaborative machine learning architecture, such that individual components iteratively swap labeled data, align feature distributions, or act as a corrective ensemble to boost overall predictive accuracy. Tags: broadly, not-comparable
    Sense id: en-Co-Trained-en-adj-tSLwH3cN Categories (other): Artificial intelligence, Machine learning, English entries with incorrect language header, English entries with language name categories using raw markup, English entries with topic categories using raw markup, English terms prefixed with co-, English terms suffixed with -ed, English terms with non-redundant non-automated sortkeys, Pages with 1 entry, Pages with entries, Artificial intelligence Disambiguation of English entries with incorrect language header: 43 57 Disambiguation of English entries with language name categories using raw markup: 36 64 Disambiguation of English entries with topic categories using raw markup: 35 65 Disambiguation of English terms prefixed with co-: 39 61 Disambiguation of English terms suffixed with -ed: 37 63 Disambiguation of English terms with non-redundant non-automated sortkeys: 30 70 Disambiguation of Pages with 1 entry: 39 61 Disambiguation of Pages with entries: 30 70 Disambiguation of Artificial intelligence: 35 65
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          "ref": "2016, S. Bianco et al., \"CURL: Image Classification using co-training...\", ScienceDirect",
          "text": "...co-trained classifiers (C). The difference between the two image representations is that one is built on the combination of all the image features..."
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          "ref": "2021, X. Huang et al., \"Deep Domain Adaptation based Cloud Type Detection...\", NASA Technical Reports Server (NTRS)",
          "text": "The l2 loss is co-trained with the correlation alignment and classifier losses in an end to end fashion..."
        },
        {
          "ref": "2026 August 6, Google DeepMind, \"WeatherNext: AI model achieves breakthrough in forecasting cyclones\"",
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          "ref": "2019, A. F. da Costa et al., \"Boosting collaborative filtering with an ensemble...\", ScienceDirect",
          "text": "In order to combine and improve the individual models generated by CoRec as they are simultaneously co-trained, ECoRec incorporates an in-built ensemble..."
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          "ref": "2022, H. Lang et al., \"Co-training Improves Prompt-based Learning for Large Language Models\", Proceedings of Machine Learning Research",
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          "ref": "2025 July 16, NVIDIA Research, \"R²D²: Training Generalist Robots with NVIDIA Research\"",
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      "ipa": "/ˌkoʊˈtɹeɪnd/"
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  "word": "Co-Trained"
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        },
        {
          "ref": "2021, X. Huang et al., \"Deep Domain Adaptation based Cloud Type Detection...\", NASA Technical Reports Server (NTRS)",
          "text": "The l2 loss is co-trained with the correlation alignment and classifier losses in an end to end fashion..."
        },
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          "ref": "2026 August 6, Google DeepMind, \"WeatherNext: AI model achieves breakthrough in forecasting cyclones\"",
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        },
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          "ref": "2022, H. Lang et al., \"Co-training Improves Prompt-based Learning for Large Language Models\", Proceedings of Machine Learning Research",
          "text": "For CB, the co-trained label model outperforms GPT-3 32-shot despite only using 4 labeled examples."
        },
        {
          "ref": "2025 July 16, NVIDIA Research, \"R²D²: Training Generalist Robots with NVIDIA Research\"",
          "text": "Even with 400 real demonstrations, the co-trained policy consistently outperforms the real-only policy by an average of 38%..."
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This page is a part of the kaikki.org machine-readable English dictionary. This dictionary is based on structured data extracted on 2026-09-06 from the enwiktionary dump dated 2026-09-02 using wiktextract (ccec6f1 and 4deed51). The data shown on this site has been post-processed and various details (e.g., extra categories) removed, some information disambiguated, and additional data merged from other sources. See the raw data download page for the unprocessed wiktextract data.

If you use this data in academic research, please cite Tatu Ylonen: Wiktextract: Wiktionary as Machine-Readable Structured Data, Proceedings of the 13th Conference on Language Resources and Evaluation (LREC), pp. 1317-1325, Marseille, 20-25 June 2022. Linking to the relevant page(s) under https://kaikki.org would also be greatly appreciated.