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i one mechanism and today i'm going to talk about are using a neural network to guide expression transformation
so imagine you are given some kind of objects such as religious cubes on which can apply transformations
and you are interested in finding pass so sequence of
transformations which can go from one configuration to another
if you blindly do that during to a problem is that the problem is that there
are so many states and it's impossible to get him visit them all blindly
so what i do in my work is that i use a neural network to guide the search and the idea is very simple so
you take two objects you feed them to the network and used output
an estimation of the number of transformation that must be applied
in order to reach the targets and uses information we can devise not go isn't that we'll really approaches solution
now in my work i'm not using rubik's cubes at my objects but mathematical expressions
and they look something like this so your valuables addition
and multiplication in addition it's expressions of focus
which is where we can apply transformations the transformations we consider our
commute activity as a city city and you should be t. v. t. v. and
also operations which moves focus on the expression to modify different part of expression
oh this is an overview of the system and it's very simple what we do is we take do expressions with a focus
we feed them to us realistically um and requesting on network and whipped in points in a
very high dimensional space and then we simply measures it the distance between those two points
so we twenties network fun fun fun six million barrels of examples of expressions
uh with distances ranging from one to ten and at the end
we obtain it system that is able to approximate the
the distance between expressions within minutes rudolph less than one
so here we see the performance of a whole system that compared to breadth first search
and we can see that our system is able to find parts between expressions um
in both cases in less than one second compared to um the efforts in two minutes
so this project is available online uh and get up at this address and was
built using tightened by george so thank you very much for your attention

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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 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 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?
Mahsa Taziki, EPFL (LPD)
7 June 2018 · 12:37 p.m.
Short IC Research Presentation 10: RaaSS Reliability as a Software Service
Maaz Mohiuddlin, LCA2, IC-EPFL
7 June 2018 · 12:40 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?
Mahsa Taziki, EPFL (LPD)
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.

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