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hello my name is then you are only pages you in in in the lab um i do my research
machine learning and one of the problems i'm working on is how to search in a database when it's hard to
describe what you're looking for in details indeed most of us here would struggle to draw
a picture of a friend accurately enough that it can be used as a aquariums for search
however if i show you two pictures of your friend of someone else you would be delayed
some increase to this is to not only for pictures but for many other things like videos music
of um fluid and so on so people are good at making comparisons now suppose
that there is a database of some comparable objects anyone's find a particular object there
but without explicitly describe what it is just to be more concrete let's say
there is um database of movie actors and you want to find this particular
i'm late on the slide if you don't remember her name but you remember how she looks like
um than what we propose in our search algorithm is to review
example from this database and ask you to choose around the object from this sample which is the most
similar to your target so which one of these four people looks more like that lady on the previous slide
and then you give us your answer would even other sample and so on until we find your target uh so that's we
um our algorithm allows you to navigate through the database by only comparing objects from
this database to target but without explicitly describe it you target um our algorithm also
uh at lawrence its own feature presentations but again only
from the comparison data and without any feature extraction methods
and in fact if you look at the two d. um features
a stadium batting of four of the features that this out with learns
uh you'll see that people who looks alike they're actually being and um clustered together
so we build up this website was that um these uh um go there and visited a um
if you want to look up forks movie actors and or just check out our search algorithm you're welcome thank

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Conference Program

Welcome address
Martin Vetterli, President of EPFL
6 June 2019 · 9:48 a.m.
James Larus, Dean of IC School, EPFL
6 June 2019 · 9:58 a.m.
Jean-Pierre Hubaux, IC Research Day co-chair
6 June 2019 · 10:07 a.m.
Adventures in electronic voting research
Dan Wallach, Professor at Rice University, Houston, USA
6 June 2019 · 10:14 a.m.
When foes are friends: adversarial examples as protective technologies
Carmela Troncoso, Assistant Professor at EPFL
6 June 2019 · 11:09 a.m.
Low-Latency Metadata Protection for Organizational Networks
Ludovic Barman, LCA1|DeDiS, EPFL
6 June 2019 · noon
Interactive comparison-based search, and
Daniyar Chumbalov, INDY 1, EPFL
6 June 2019 · 12:06 p.m.
Decentralized, Secure and Verifiable Data Sharing
David Froelicher, LCA1|DeDiS, EPFL
6 June 2019 · 12:09 p.m.
Communication Efficient Decentralised Machine Learning
Anastasia Koloskova, MLO, EPFL
6 June 2019 · 12:11 p.m.
Detecting the Unexpected via Image Resynthesis
Krzysztof Lis, CVLab, EPFL
6 June 2019 · 12:14 p.m.
Sublinear Algorithms for Graph Processing
Aida Mousavifar, THL4, EPFL
6 June 2019 · 12:16 p.m.
Protecting the Metadata of Your Secret Messages
Kirill Nikitin, DEDIS, EPFL
6 June 2019 · 12:18 p.m.
Teaching a machine learning algorithm faster
Farnood Salehi, INDY 2, EPFL
6 June 2019 · 12:21 p.m.
Secure Microarchitectural Design
Atri Bhattacharyya, PARSA/HexHive, EPFL
6 June 2019 · 12:23 p.m.
Security testing hard to reach code
Mathias Payer, Assistant Professor at EPFL
6 June 2019 · 1:50 p.m.
Best Research Presentation Award Ceremony
Bryan Ford, Jean-Pierre Hubaux, Deirdre Rochat, EPFL
6 June 2019 · 3:54 p.m.