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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Speaker: Sivan Sabato
Title: Auditing: Active Learning with Outcome-Dependent Query Costs
Abstract: We propose a learning setting in which unlabeled data is free, and the cost of a label depends on its value, which is not known in advance. Specifically, we study binary classification in an extreme case, where the algorithm only pays for negative labels. Our motivation is applications such as fraud detection, in which investigating an honest transaction should be avoided if possible. We term the setting "auditing", and consider the "auditing complexity" of an algorithm. We design auditing algorithms for simple hypothesis classes,
and show that with these algorithms, the auditing complexity can be significantly lower than the active label complexity. We also consider a general competitive approach for auditing,
and demonstrate its potential for linear classification.
Joint work with Anand Sarwate and Nati Srebro from TTI-Chicago
