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CATEGORIES:Women@CL Events
SUMMARY:women@CL Talklet Event - Sandra Servia\, Ca
talina Cangea\, Angeliki Koutsoukou-Argyraki
DTSTART;TZID=Europe/London:20180525T130000
DTEND;TZID=Europe/London:20180525T140000
UID:TALK106345AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/106345
DESCRIPTION:*Title:* Mobile sensing at the service of mental w
ellbeing\n\n*Abstract*\n\nThe pervasiveness of sma
rtphones and their rich-set of built-in sensors\,
including accelerometer\, GPS and microphone\, hav
e allowed the emergence of many platforms to passi
vely monitor health and behaviour through experien
ce sampling and sensing\, at low cost and large sc
ale. However\, studies at the confluence of mental
health and mobile sensing have been longitudinall
y limited\, controlled\, and confined to a small n
umber of participants. In this talk\, I will repor
t on what we believe is the largest longitudinal\,
in-the-wild study of mood through smartphones\, w
hich includes data from ~18\,000 participants for
a period of three years. Using data collected with
an Android app\, which includes self-reported moo
ds\, system triggered experience sampling data and
passive sensing data\, we are able to identify ro
utines and their relation with demographics\, perc
eived health and psychological traits\, as well as
exploring the predictability of usersâ€™ mood from
passive sensing data. Although this large scale da
ta collection is very suitable for population stud
ies\, the collection and use of sensitive data com
es with privacy issues and chances of data misuses
. In this line\, I will comment on the trade-offs
between utility\, battery consumption and latency
of private-by-design mobile health apps that rely
on on-device processing with limited cloud offload
ing.\n\n------------------------------------------
------------\n\n\n*Title:* Cross-modal techniques
for data integration\n\n*Abstract*\n\nMultimodal l
earning is a natural and necessary progression fro
m the traditional methods that typically learn to
represent a single modality. \nApplications exist
in a variety of scenarios\, a few notable examples
being medicine\, environmental risk and robotics.
In this talk\, I will present two classification
tasks from the audiovisual and chemical domains\,
along with the deep learning architectures that I
have designed to improve on existing methods.\n\n\
n-------------------------------------------------
----------\n\n\n*Title:* Proof Mining Mathematics\
, Formalizing Mathematics-the ALEXANDRIA project\n
\n*Abstract*\n\nProof mining is a research program
in applied proof theory involving the extraction
of quantitative\, computable information from (eve
n\nnonconstructive) mathematical proofs of stateme
nts of a certain logical form\, via a pen-and-pape
r i.e. \\textit{not} automated logical analysis. \
nThe program originated as ``unwinding of proofs
'' in the ideas of \nGeorg Kreisel from the fiftie
s\, and has been developed by Ulrich Kohlenbach an
d his collaborators during the past two decades.\n
A great deal of applications for proofs in differe
nt research directions in Mathematics has been ac
hieved.\nALEXANDRIA is a new ERC project at the U
niversity of Cambridge under the leadership of La
wrence Paulson aiming at the creation of a proof d
evelopment environment for working mathematicians
through a collaboration of mathematicians and comp
uter scientists. This will be achieved by formaliz
ing mathematical proofs with the proof assistant \
\textit{Isabelle}.\nThe focus of the project is th
e management and use of large-scale mathematical k
nowledge\, both as theorems and as algorithms.\nIn
addition to the obvious importance of proof verif
ication for Mathematics and the usefulness of libr
aries of formalized proofs for (the future generat
ions of) mathematicians\, the formalization of mat
hematical proofs could possibly shed light on inte
resting proof theoretic questions. Moreover\, enri
ching the libraries with formalized proof-mined pr
oofs could open the way for the exciting prospect
of automating proof mining itself.\n
LOCATION:Computer Laboratory\, William Gates Building\, Roo
m SS03
CONTACT:Ayat Fekry
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