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was so yeah i am so everybody's talking about it obviously eh um
and we collecting more and more of it if for a study by in c. for 'cause the by twenty twenty will have
like thirty five that abides of machine generated data but the essence of collecting data is getting inside out of it
and that's we're introducing new applications is application sort of exploratory nature which means
that they are dynamic so we don't know a priori what kind of
workload work on that the sort order banning gone and also that the queries
depend on the data as well as the result of prior queries
examples have thought such applications are um uh scientists exploration applications such as this remembering
project or astronomical observation experiments as well as modern in terms of things application
what the user does not know exactly searching for what he's looking for interesting part
and these are the the increasing data collections as well as these exploratory nature of modern applications
creates new challenges for data processing system specifically the user
wants instant access to data so multi processing time
also the the uh the product either the user relies on
the interactive query response time and finally increasing data size
also increases the the requirements for storage and computation applications
so coming up with cost efficient storage interpretation solutions is another charge
with the face but let us see why these actually problem
so a conventionally in order to explore date out scientists to use databases
and however introduction to start quitting you have the first load anything's
the beta indices are essentially a and read on the end of
the lady that structures which make known data access parts faster
eh it however eh the what what is the trouble is that in actually to
load in in this data this preparing the preparing step is very time consuming
on the right hand side you actually see the can will that execution
time for a executing game i interned of things work load
and what we see is that um see how the user has actually to load anything so they dubbed the
grey line which shows agree time is uh is starts up high since it contains the processing time
a a in my in my research uh uh yeah in my research what i do is actually um try it it
it would it and into into it you enable the existing
query engines with interactive capability a interact the expiration capabilities
by taking advantage of the underlying data distributions and i uh adapting to the work we work out why run queries
you know what she's that i eh develop online tuning algorithms which a body in a build
overlay data structures as byproduct of quick secretion and also by reducing the result decision requirements
eh tool by by doing that we actually remove the
requirement for preprocessing we reduce the storage overhead
and we enable the the the user to explore data efficiently while

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Conference program

Welcome address
Andreas Mortensen, Vice President for Research, EPFL
7 June 2018 · 9:49 a.m.
Introduction
Jim Larus, Dean of IC School, EPFL
7 June 2018 · 10 a.m.
The Young Software Engineer’s Guide to Using Formal Methods
K. Rustan M. Leino, Amazon
7 June 2018 · 10:16 a.m.
Safely Disrupting Computer Networks with Software
Katerina Argyraki, EPFL
7 June 2018 · 11:25 a.m.
Short IC Research Presentation 2: Gamified Rehabilitation with Tangible Robots
Arzu Guneysu Ozgur, EPFL (CHILI)
7 June 2018 · 12:15 p.m.
Short IC Research Presentation 3: kickoff.ai
Lucas Maystre, Victor Kristof, EPFL (LCA)
7 June 2018 · 12:19 p.m.
Short IC Research Presentation 5: CleanM
Stella Giannakopoulo, EPFL (DIAS)
7 June 2018 · 12:25 p.m.
Short IC Research Presentation 6: Understanding Cities through Data
Eleni Tzirita Zacharatou, EPFL (DIAS)
7 June 2018 · 12:27 p.m.
Short IC Research Presentation 7: Datagrowth and application trends
Matthias Olma, EPFL (DIAS)
7 June 2018 · 12:31 p.m.
Short IC Research Presentation 8: Point Cloud, a new source of knowledge
Mirjana Pavlovic, EPFL (DIAS)
7 June 2018 · 12:34 p.m.
Short IC Research Presentation 9: To Click or not to Click?
Eleni Tzirita Zacharatou, EPFL (DIAS)
7 June 2018 · 12:37 p.m.
20s pitch 1: Cost and Energy Efficient Data Management
Utku Sirin, (DIAS)
7 June 2018 · 2:20 p.m.
20s pitch 2: Gamification of Rehabilitation
Arzu Guneysu Ozgur, EPFL (CHILI)
7 June 2018 · 2:21 p.m.
20s pitch 4: Neural Network Guided Expression Transformation
Romain Edelmann, EPFL (LARA)
7 June 2018 · 2:21 p.m.
20s pitch 5: Unified, High Performance Data Cleaning
Stella Giannakopoulo, EPFL (DIAS)
7 June 2018 · 2:21 p.m.
20s pitch 6: Interactive Exploration of Urban Data with GPUs
Eleni Tzirita Zacharatou, EPFL (DIAS)
7 June 2018 · 2:22 p.m.
20s pitch 7: Interactive Data Exploration
Matthias Olma, EPFL (DIAS)
7 June 2018 · 2:22 p.m.
20s pitch 8: Efficient Point Cloud Processing
Mirjana Pavlovic, EPFL (DIAS)
7 June 2018 · 2:23 p.m.
20s pitch 9: To Click or not to Click?
Eleni Tzirita Zacharatou, EPFL (DIAS)
7 June 2018 · 2:24 p.m.
20s pitch 10: RaaSS Reliability as a Software Service
Maaz Mohiuddlin, LCA2, IC-EPFL
7 June 2018 · 2:24 p.m.
20s pitch 11: Adversarial Machine Learning in Byzantium
El Mahdi El Mhamdi, EPFL (LPD)
7 June 2018 · 2:24 p.m.
Machine Learning: Alchemy for the Modern Computer Scientist
Erik Meijer, Facebook
7 June 2018 · 2:29 p.m.

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