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Mobile advertising has recently seen dramatic growth, fueled by the global proliferation of mobile phones and devices. The task of predicting ad response is thus crucial for maximizing business revenue. However, ad response data change dynamically over time, and are subject to cold-start situations in which limited history hinders reliable prediction. There is also a need for a robust regression estimation for high prediction accuracy, and good ranking to distinguish the impacts of differentdoi:10.1145/2556195.2556240 dblp:conf/wsdm/OentaryoLLLF14 fatcat:zv7f6zvie5hzhhzn5fpawhiqqu