What we're about
Take a look at material from past meetups in our associated Github Repo (https://github.com/suhailshergill/differential-privacy).
Also come discuss ideas with like-minded individuals in our Gitter Chatroom (https://gitter.im/suhailshergill/differential-privacy).
Per its wikipedia page, Differential Privacy aims to provide means to maximize the accuracy of queries from statistical databases while minimizing the chances of identifying its records. Companies such as Apple Inc. seem to be using it (https://www.wired.com/2016/06/apples-differential-privacy-collecting-data/).
The goal of this meetup is to look at the current state of the art in terms of algorithms, implementations and applications of differential privacy techniques as well as state of the art in performing statistical analyses while providing differentially private guarantees.
- Differential Privacy blog mini-series (http://www.win-vector.com/blog/2015/11/our-differential-privacy-mini-series/)
- http://www.cs.cmu.edu/afs/cs/academic/class/15859m-s11/ww... (http://www.cs.cmu.edu/afs/cs/academic/class/15859m-s11/www/lectures/lect0420.pdf)
- The Algorithmic Foundations of Differential Privacy ("Privacy book") (https://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf)
- New Statistical Applications for Differential Privacy (thesis) (http://www.cs.cmu.edu/~rjhall/thesis.pdf)
NOTE: We are in need of sponsors who would be willing to lend a hand in hosting meetups. Please contact the organizer.