Robust multi-item auction design using statistical learning: Overcoming uncertainty in bidders' types distributions

This paper presents a novel mechanism design for multi-item auction settings with uncertain bidders' type distributions. Our proposed approach utilizes nonparametric density estimation to accurately estimate bidders' types from historical bids, and is built upon the Vickrey-Clarke-Groves (...

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Bibliographische Detailangaben

Hauptverfasser:	Han, Jiale, Dai, Xiaowu
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Computer Science and Game Theory Statistics - Machine Learning
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