Crowdsourcing: Quality Management and Scalability
                         Panos Ipeirotis
                       New York University

I will discuss the use of crowdsourcing for building machine learning
models quickly and under budget constraints, with a focus on the case
where humans are noisy and the of "labels" provided by humans for data
items are imperfect. I will present strategies of managing quality in
a crowdsourcing environment, showing in parallel how to integrate data
acquisition with the process of learning machine learning models.  I
illustrate the results using real- life applications drawn from the
field of online advertising. Time permitting, I will also discuss our
latest results showing that mice and Mechanical Turk workers are not
that different after all.