Differential privacy is an interesting research area. I know there have been several survey talks, including at NIPS. I wanted to point out this: http://rsrg

Differential privacy is an interesting research area. I know there have been several survey talks, including at NIPS. I wanted to point out this: http://rsrg.cms.caltech.edu/netecon/privacy2015/program.shtml http://rsrg.cms.caltech.edu/netecon/privacy2015/program.shtm... which has some nice slides and discussion on the "reusable holdout" ("thresholdout") which is a technique to allow one to use all of the training data to fit a lot of models, but also offers guarantees against overfitting.