MINES ParisTech, PSL Research University, France
Abstract:We describe jsCcoq, a new platform and user environment for the Coq interactive proof assistant. The jsCoq system targets the HTML5-ECMAScript 2015 specification, and it is typically run inside a standards-compliant browser, without the need of external servers or services. Targeting educational use, jsCoq allows the user to start interaction with proof scripts right away, thanks to its self-contained nature. Indeed, a full Coq environment is packed along the proof scripts, easing distribution and installation. Starting to use jsCoq is as easy as clicking on a link. The current release ships more than 10 popular Coq libraries, and supports popular books such as Software Foundations or Certified Programming with Dependent Types. The new target platform has opened up new interaction and display possibilities. It has also fostered the development of some new Coq-related technology. In particular, we have implemented a new serialization-based protocol for interaction with the proof assistant, as well as a new package format for library distribution.
Abstract:We present a practical, differentially private algorithm for answering a large number of queries on high dimensional datasets. Like all algorithms for this task, ours necessarily has worst-case complexity exponential in the dimension of the data. However, our algorithm packages the computationally hard step into a concisely defined integer program, which can be solved non-privately using standard solvers. We prove accuracy and privacy theorems for our algorithm, and then demonstrate experimentally that our algorithm performs well in practice. For example, our algorithm can efficiently and accurately answer millions of queries on the Netflix dataset, which has over 17,000 attributes; this is an improvement on the state of the art by multiple orders of magnitude.