title: Signal Processing and Machine Learning with Differential Privacy: Algorithms and challenges for continuous data.
authors.affiliation: Toyota Technological Institute at Chicago. He received B.S. degrees in electrical engineering and mathematics from the Massachusetts Institute of Technology in 2002 and a Ph.D. degree in electrical engineering from the University of California at Berkeley in 2008. His research is on distributed signal processing, optimization, machine learning, information theory, and statistics. ( asarwate@ttic.edu ).
authors.forename: Anand D
authors.initials: AD
authors.lastname: Sarwate
authors.affiliation: Department of Computer Science and Engineering, University of California, San Diego. She received a bachelor of technology degree in computer science and engineering from the Indian Institute of Technology, Kanpur, in 2002, and a Ph.D. degree in computer science from the University of California at Berkeley in 2007. Her research focuses on the design and analysis of machine-learning algorithms and their applications. In particular, she is interested in privacy-preserving machine learning, where the goal is to develop machine-learning methods for sensitive data while still preserving the privacy of the individuals in the data set. ( kchaudhuri@ucsd.edu ).
authors.forename: Kamalika
authors.initials: K
authors.lastname: Chaudhuri
references.citation: Adv Neural Inf Process Syst. 2010;23:1696-1704
references.pmid: 21451738
references.citation: J Mach Learn Res. 2011 Mar;12:1069-1109
references.pmid: 21892342
references.citation: Proc Int Conf Mach Learn. 2012 Jul;2012:1327-1334
references.pmid: 25302341
references.citation: Adv Neural Inf Process Syst. 2012 Dec;25:3113-3121
references.pmid: 26273181