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  "author": "Carlos Fern\u00e1ndez-Lor\u00eda",
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  "author": "Carlos Fern\u00e1ndez-Lor\u00eda",
            
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  "author_email": "",
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  "defined_in": "https://doi.org/10.48550/arXiv.2206.12532",
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  "defined_in": "https://doi.org/10.48550/arXiv.2206.12532",
            
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  "doi": "10.57702/u3yiur9e",
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  "doi": "10.57702/u3yiur9e",
            
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  "doi_date_published": null,
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  "doi_date_published": "2024-12-16",
            
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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": "Hong Kong University of Science and 
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      "extra_author": "Hong Kong University of Science and 
            
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Technology",
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Technology",
            
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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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    {
            
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      "extra_author": "Jorge Lor\u00eda",
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      "extra_author": "Jorge Lor\u00eda",
            
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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": "Purdue University",
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      "extra_author": "Purdue University",
            
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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": "Advertising",
            
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      "name": "advertising",
            
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      "title": "Advertising"
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      "title": "Advertising"
            
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    {
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    {
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Uplift Modeling",
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      "display_name": "Uplift Modeling",
            
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      "name": "uplift-modeling",
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      "name": "uplift-modeling",
            
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      "title": "Uplift Modeling"
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      "title": "Uplift Modeling"
            
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"https://ailab.criteo.com/criteo-uplift-prediction-dataset/",
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"https://ailab.criteo.com/criteo-uplift-prediction-dataset/",
            
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  "metadata_modified": "2024-12-16T23:28:16.292921",
            
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  "name": "criteo-uplift-prediction-dataset",
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  "name": "criteo-uplift-prediction-dataset",
            
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  "notes": "The dataset used in the paper is a large-scale advertising 
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  "notes": "The dataset used in the paper is a large-scale advertising 
            
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dataset, which includes 13,979,592 rows, each representing a user with 
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dataset, which includes 13,979,592 rows, each representing a user with 
            
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11 features, a treatment indicator for the ad, and the labels (visits 
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11 features, a treatment indicator for the ad, and the labels (visits 
            
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and conversions).",
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and conversions).",
            
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  "title": "Criteo Uplift Prediction Dataset",
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}