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  "access_rights": "",
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  "author": "Young Hun Jung",
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  "author": "Young Hun Jung",
            
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  "author_email": "",
            
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  "defined_in": "https://doi.org/10.48550/arXiv.1710.08079",
            
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  "doi": "10.57702/ktkum9xh",
            
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  "doi_date_published": null,
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  "doi_date_published": "2025-01-02",
            
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  "extra_authors": [
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  "extra_authors": [
            
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    {
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    {
            
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      "extra_author": "Ambuj Tewari",
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      "extra_author": "Ambuj Tewari",
            
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      "orcid": ""
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      "orcid": ""
            
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    }
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      "description": "",
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      "description": "",
            
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      "display_name": "Multi-Label Learning",
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      "name": "multi-label-learning",
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      "name": "multi-label-learning",
            
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      "title": "Multi-Label Learning"
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      "title": "Multi-Label Learning"
            
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    },
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    {
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    {
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Ranking",
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      "display_name": "Ranking",
            
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      "name": "ranking",
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      "name": "ranking",
            
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      "title": "Ranking"
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      "title": "Ranking"
            
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  "name": "online-boosting-algorithms-for-multi-label-ranking",
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  "name": "online-boosting-algorithms-for-multi-label-ranking",
            
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  "notes": "We consider the multi-label ranking approach to 
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  "notes": "We consider the multi-label ranking approach to 
            
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multi-label learning. Boosting is a natural method for multi-label 
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multi-label learning. Boosting is a natural method for multi-label 
            
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ranking as it aggregates weak predictions through majority votes, 
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ranking as it aggregates weak predictions through majority votes, 
            
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which can be directly used as scores to produce a ranking of the 
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which can be directly used as scores to produce a ranking of the 
            
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labels.",
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labels.",
            
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      "display_name": "boosting",
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      "id": "76506887-f1a7-4745-85de-ea8d371164fa",
            
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      "name": "multi-label learning",
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      "name": "multi-label learning",
            
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      "display_name": "multi-label ranking",
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      "display_name": "multi-label ranking",
            
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      "id": "c8ca4246-8a05-4487-9c0b-b9621f4dbf63",
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      "id": "c8ca4246-8a05-4487-9c0b-b9621f4dbf63",
            
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      "name": "multi-label ranking",
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      "name": "multi-label ranking",
            
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      "state": "active",
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    }
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    }
            
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  ],
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  "title": "Online Boosting Algorithms for Multi-label Ranking",
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  "title": "Online Boosting Algorithms for Multi-label Ranking",
            
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  "type": "dataset",
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  "version": ""
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  "version": ""
            
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}
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}