Leakage in data mining: Formulation, detection, and avoidance von Kaufman, Shachar, Rosset, Saharon, Perlich, Claudia, Stitelman, Ori

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Machine Learning and Knowledge Discovery in Databases Part VII: Applied Data Science and Demo Track : European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proc... von Morales, Gianmarco De Francisci, Perlich, Claudia, Ruchansky, Natali, Kourtellis, Nicolas, Baralis, Elena, Bonchi, Francesco

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Machine Learning and Knowledge Discovery in Databases Part VI: Applied Data Science and Demo Track : European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proce... von Morales, Gianmarco De Francisci, Perlich, Claudia, Ruchansky, Natali, Kourtellis, Nicolas, Baralis, Elena, Bonchi, Francesco

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Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part VII von De Francisci Morales, Gianmarco, Perlich, Claudia, Ruchansky, Natali, Kourtellis, Nicolas, Baralis, Elena, Bonchi, Francesco

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Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part VI von De Francisci Morales, Gianmarco, Perlich, Claudia, Ruchansky, Natali, Kourtellis, Nicolas, Baralis, Elena, Bonchi, Francesco

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Tree Induction vs. Logistic Regression: A Learning-Curve Analysis von Perlich, Claudia, Provost, Foster, Simonoff, Jeffrey S

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Distribution-based aggregation for relational learning with identifier attributes von Perlich, Claudia, Provost, Foster

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Evaluating and Optimizing Online Advertising: Forget the Click, but There Are Good Proxies von Dalessandro, Brian, Hook, Rod, Perlich, Claudia, Provost, Foster

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Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, P...

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Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, P...

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Target-Aware Molecular Graph Generation von Tan, Cheng, Gao, Zhangyang, Li, Stan Z.

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Multivariate Time-Series Anomaly Detection with Temporal Self-supervision and Graphs: Application to Vehicle Failure Prediction von Hojjati, Hadi, Sadeghi, Mohammadreza, Armanfard, Narges

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Bigger is Better, but at What Cost? Estimating the Economic Value of Incremental Data Assets von Dalessandro, Brian, Perlich, Claudia, Raeder, Troy

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Continually Learning Out-of-Distribution Spatiotemporal Data for Robust Energy Forecasting von Prabowo, Arian, Chen, Kaixuan, Xue, Hao, Sethuvenkatraman, Subbu, Salim, Flora D.

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Contrastive Learning-Based Imputation-Prediction Networks for In-hospital Mortality Risk Modeling Using EHRs von Liu, Yuxi, Zhang, Zhenhao, Qin, Shaowen, Salim, Flora D., Yepes, Antonio Jimeno

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PDF-VQA: A New Dataset for Real-World VQA on PDF Documents von Ding, Yihao, Luo, Siwen, Chung, Hyunsuk, Han, Soyeon Caren

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Semi-Supervised Social Bot Detection with Initial Residual Relation Attention Networks von Zhou, Ming, Feng, Wenzheng, Zhu, Yifan, Zhang, Dan, Dong, Yuxiao, Tang, Jie

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DegUIL: Degree-Aware Graph Neural Networks for Long-Tailed User Identity Linkage von Long, Meixiu, Chen, Siyuan, Du, Xin, Wang, Jiahai

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Interactive Visualization of Counterfactual Explanations for Tabular Data von Guyomard, Victor, Fessant, Françoise, Guyet, Thomas, Bouadi, Tassadit, Termier, Alexandre

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Context-Aware Deep Time-Series Decomposition for Anomaly Detection in Businesses von Nam, Youngeun, Trirat, Patara, Kim, Taeyoon, Lee, Youngseop, Lee, Jae-Gil

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