[Lisa_seminaires] Fwd: C'est celui-là, Yoshua,

Yoshua Bengio yoshua.umontreal at gmail.com
Sam 29 Oct 12:07:07 EDT 2016


Please all come to this talk (in English) Wednesday 3:30pm @ 6214, by
Augustin Chaintreau from Columbia.

-------- Forwarded Message --------
Subject: colloque DIRO *mercredi* 2 nov, Augustin Chaintreau (Columbia)
Date: Sat, 29 Oct 2016 11:32:53 -0400
From: Pierre McKenzie <mckenzie at iro.umontreal.ca>
<mckenzie at iro.umontreal.ca>
To: seminaires at iro.umontreal.ca

*Fixing our Opaque, Fragmented and Disparate Big Data*

par


*Augustin Chaintreau *

 Columbia University

*Mercredi 2 novembre, 15:30-16:30*, *Salle 6214*, Pavillon André-Aisenstadt

    Université de Montréal, 2920 Chemin de la Tour



The conference will be held in English.

*ATTENTION: *horaire et salle inhabituels pour un colloque du DIRO.

*Résumé *

Today's big data is flawed, and the threats it poses are not theoretical:
We show with reproducible experiments that personalization algorithms in
services used by millions pose moral hazards, that metrics of social
endorsement are vastly misleading, and that the network dynamics
facilitated by online interactions and sharing economies stand in the way
of reducing various inequalities. Personal information collection and
usage, however, ultimately bring benefits that we cannot forego, including
in areas such as health, energy efficiency and public policies.

Opacity, Fragmented Views, and Disparate Impact may appear embedded in the
fabric of Big Data; we show, on the contrary, from multiple examples that
these trends can be reversed. Our first challenge is transparency and
accountability in today's personalization, for which we provide a scalable
solution validated on three leading services. We then address how to
leverage opportunities offered by personal data in different domains, while
informing mobile consumers and social media participants on their risks.
Finally, we model how parsimonious individuals disparately benefit from
information shared locally on a social network. Our analysis reveals
general conditions on a network spectral expansion to eventually benefit
all its members, closely related to the presence to special segregations
between groups of users.



*Biographie*

Augustin is an Assistant Professor of Computer Science at Columbia
University since 2010, where he directs the Mobile Social Lab. The goal of
his research is to reconcile the benefits of leveraging personal data and
social networks with a commitment to fairness and privacy. His latest
results address transparency in personalization, the role of human mobility
in privacy across several domains, the efficiency of crowdsourced content
curation, the fairness of incentives to share personal data. His research
lead to 25 papers in tier-1 conferences (five receiving best or best
student paper awards at ACM CoNEXT, SIGMETRICS, USENIX IMC, IEEE MASS,
Algotel), covered by several media including the NYT blog, The Washington
Post, the Economist, or The Guardian. An ex student of the Ecole Normale
Supérieure in Paris, he earned a Ph.D in mathematics and computer science
in 2006, a NSF CAREER Award in 2013 and the ACM SIGMETRICS Rising star
award in 2013. He has been an active member of network and web research
community, organizing the upcoming Data Transparency Lab Conference,
serving in the program committees of ACM SIGMETRICS (as chair), SIGCOMM,
WWW, CoNEXT (as chair), MobiCom, MobiHoc, IMC, WSDM, WWW, COSN, AAAI ICWSM,
and IEEE Infocom, and as area editor for IEEE TMC, ACM SIGCOMM CCR, and ACM
SIGMOBILE MC2R.
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