mpla.math.uoa.gr
Font size: Αα Αα Αα hide gadgets
You are here: Defenses » February 2017 » Agamemnon Giannakopoulos Anonymously browsing from 54.145.117.60 at 07:07:35, 19-11-2017. login
download defense details: { pdf }

MSc thesis defense presentation

Agamemnon Giannakopoulos defends his MSc thesis

Date: Tuesday, 28 Feb 2017
Time: 16:00
Location: School of Electrical and Computer Engineering (old buildings), 1.1.31
Thesis title: Learning Poisson Binomial Distributions with Differential Privacy
Committee:

Thesis abstract

This thesis tries to leverage two major research areas. The first area concerns the Distribution Learning Theory and the second the Differential Privacy. More specific, given a highly efficient algorithm which learns with ε-accuracy a Poisson Binomial Distribution we try to study its Differential Privacy property. We show that the Algorithm achieves Differential Privacy under specific circumstances (regarding PBD nature). If the PBD close to a (n,k)-Binomial form the algorithm is Differential Privacy. If the PBD is close to a k-sparse form algorithm's privacy depends on PBD cardinality.

Reporter

Page updates

No recent updates.

Feeds RSS and Atom feeds

posts
all posts RSS
news RSS
announcements RSS
website news RSS
events
all events RSS
defenses RSS
exams RSS
seminars RSS
graduations RSS
Web standards: XHTML1.0, CSS3.
© 1996 – 2017 MPLA: Graduate program in Logic, Algorithms and Computation.
Contact the webmaster.