![[Search]](/static/images/search.gif){kind=small}
![[A-Z Index]](/static/images/az.gif){kind=small}
![[Contact]](/static/images/contact.gif){kind=small}
![[University of Cambridge]](/static/images/identifier2.gif){kind=small}
![[Talks.cam]](/static/images/talkslogosmall.gif)
Grigorios Loukides (Cardiff University)
Thursday 08 December 2016, 15:30-16:00
Anonymization of high-dimensional datasets
- đ¤ Speaker: Grigorios Loukides (Cardiff University)
- đ Date & Time: Thursday 08 December 2016, 15:30 - 16:00
- đ Venue: Seminar Room 1, Newton Institute
Abstract
Organizations collect increasing amounts of high-dimensional data about individuals. Examples are health record datasets containing diagnosis information, marketing datasets containing products purchased by customers, and web datasets containing check-ins in social networks. The sharing of such data is increasingly needed to support applications and/or satisfy policies and legislation. However, the high dimensionality of data makes their anonymization difficult, both from an effectiveness and from an efficiency point of view. In this talk, I will illustrate the problem and briefly review the main techniques used in the anonymization of high-dimensional data. Subsequently, I will present a class of methods we have been developing for anonymizing complex, high-dimensional data and their application to the healthcare domain.
Series This talk is part of the Isaac Newton Institute Seminar Series series.
Included in Lists
- All CMS events
- bld31
- Cambridge Centre for Data-Driven Discovery (C2D3)
- Cambridge talks
- Chris Davis' list
- dh539
- Featured lists
- INI info aggregator
- Interested Talks
- Isaac Newton Institute Seminar Series
- ndk22's list
- ob366-ai4er
- rp587
- School of Physical Sciences
- Seminar Room 1, Newton Institute
- Trust & Technology Initiative - interesting events
- yk449
Note: Ex-directory lists are not shown.