CSEC, Erskine Williamson Building access via JCMB Kings Buildings, University of Edinburgh
Large technology companies rely on collecting data from their users to understand their interests, and better customize the company's products. Increasingly, this must be done while preserving individual users' privacy. Recently, techniques based on randomization and data sketching have been adopted to provide data collection protocols which optimize the privacy-accuracy tradeoff. In this talk, I'll discuss methods deployed by Google and Apple to collect frequency information, and our recent work to capturing information on marginal and cumulative distributions.
Graham Cormode is a Professor in Computer Science at the University of Warwick and the Alan Turing Institute's University Liaison Director for Warwick. He works on research topics in data management, privacy and big data analysis. Previously he was a principal member of technical staff at AT&T Labs-Research in the USA. He serves as an associate editor for AVM Transactions on Database Systems (TODS), and the Journal of Discrete Algortithms.
This is joint work with Tejas Kulkarni and Divesh Srivastava.