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  "author": "Yang Zhang",
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  "author": "Yang Zhang",
            
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  "defined_in": "https://doi.org/10.48550/arXiv.1608.06608",
            
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  "doi": "10.57702/mtwcehr7",
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  "doi": "10.57702/mtwcehr7",
            
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  "doi_date_published": "2024-12-16",
            
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  "extra_authors": [
            
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    {
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    {
            
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      "extra_author": "Rupam Acharyya",
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      "extra_author": "Rupam Acharyya",
            
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      "orcid": ""
            
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    },
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    {
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      "extra_author": "Ji Liu",
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      "extra_author": "Ji Liu",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    {
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    {
            
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      "extra_author": "Boqing Gong",
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      "extra_author": "Boqing Gong",
            
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      "orcid": ""
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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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  "notes": "The dataset used in the paper is a synthetic dataset for 
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  "notes": "The dataset used in the paper is a synthetic dataset for 
            
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in\ufb01nite-label learning. It consists of 500 training data points 
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in\ufb01nite-label learning. It consists of 500 training data points 
            
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and 1000 testing data points from a \ufb01ve-component Gaussian 
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and 1000 testing data points from a \ufb01ve-component Gaussian 
            
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mixture model. The dataset also includes 10 seen labels and 2990 
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mixture model. The dataset also includes 10 seen labels and 2990 
            
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unseen labels.",
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unseen labels.",
            
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  "title": "Synthetic dataset for in\ufb01nite-label learning",
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  "title": "Synthetic dataset for in\ufb01nite-label learning",
            
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}