Machine Learning enables us to discover patterns from data and make predictions/decisions directly from the data we have. It has been a workhorse which is widely used in biomedical, industry engineering, economics and other area.However, in some real world application, especially in economics, the data collection is not an ideal and free process.For one thing, respondents may lie about their answer for the questions because the question includes their sensitive information or they want to interfere the learning model on purpose; for another thing, collecting data will cost money according to their collection approach,contents of data and other facts. Thus recent years, there are many works with this kind of strategic considerations like how to elicit true answers from respondents, how to make learning algorithm more robust when confronted with strategic answers, and how to make the learning algorithm accurate with lowest cost. In this project, you are expected to do a literature survey on relevant papers, taste a ﬂavor on how scientists deal with real world problem with mathematical models and try to propose (and realize) your own model.
Duration: 3 weeks (From 2016-10-10 to 2016-10-30)
Estimated workload: 8-12 hours/week
The final score is peer-review score (30%) plus project host score (70%)
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