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A Summary of the Google Zürich Algorithms & Optimization Workshop
viernes, 23 de febrero de 2018
Posted by Silvio Lattanzi, Research Scientist, Google Zürich and Vahab Mirrokni, Research Scientist, Google New York
Recently, we hosted a
workshop on Algorithms and Optimization
in our office in Zürich, with the goal of fostering collaboration between researchers from
academia
and
Google
by providing a forum to exchange ideas in machine learning theory and large-scale graph mining. As part of the topics discussed, we additionally highlighted our aim to build a group similar to the
NYC algorithms research team
in Google’s Zürich office.
Silvio Lattanzi presenting the work of the Graph Mining team
The workshop was structured in five sessions (see the full agenda
here
), each consisting of talks by attendees that touched the following research areas:
Market Algorithms:
This session included five talks upon problems related to optimizing online marketplaces and repeated auctions.
Vahab Mirrokni
(Google New York) opened the session with an overview talk about
market algorithms project
, then
Paul Duetting
(London School of Economics) presented
recent advancement in stochastic optimization for pricing
.
Renato Paes Leme
(Google New York) spoke about dynamic auctions in practice.
Stefano Leonardi
(Sapienza University of Rome) presented the challenges arising from the
Reservation Exchange Markets
and finally
Radu Jurca
(Google Zürich) explained how to pack YouTube Reservation Ads.
Machine Learning Theory:
Our second session focused on theoretical aspects of machine learning research.
Olivier Bousquet
(Google Brain Team, Zürich) opened the session discussing challenges in
agnostic learning of distribution
. Then
Amin Karbasi
(Yale) and
Andreas Krause
(ETH Zürich) presented recent results on
submodular optimization
and
learning submodular models
.
Martin Jaggi
(EPFL) explained new technique to parallelize optimization algorithms. And finally
Nicolò Cesa-Bianchi
(Università degli Studi di Milano) presented
new results on bandits
.
Large-scale Graph Mining:
In this session, we presented some of our achievements and challenges in the context of large-scale graph mining project.
Silvio Lattanzi
(Google Zürich) opened the session describing the applied and theoretical work of the
Graph Mining team
. Then
Piotr Sankowski
(University of Warsaw) presented an
interesting model to explain the size of cascades in real-world graphs
.
Thomas Sauerwald
(University of Cambridge) presented some new results on
Coalescing Random Walks
and
Peter Sanders
(Karlsruhe Institute of Technology) presented several interesting results in
algorithm engineering for large datasets
. After this talk, we brainstormed with Peter Sanders and Christian Schulz (University of Vienna) on different techniques to produce balanced graph partitioning results that would beat the quality of cuts generated in a
recent paper
. We are looking forward to seeing the improved results.
Privacy and Fairness:
This session covered new topics concerning privacy-preserving algorithms, and fairness in machine learning and recommender systems. Both of these topics are among the main areas of concern in machine learning. For example,
Sergei Vassilvitskii
(Google New York) presented new algorithm to compute fair clustering and
Elisa Celis
(EPFL) discussed several aspects of Algorithmic fairness and Bias in Machine learning.
Florin Ciocan
(INSEAD) described algorithms for
fair allocation
and
Graham Cormode
(University of Warwick) presented
algorithms for private release of marginal statistics
.
Sketching, Hashing, and Dynamic Algorithms:
Finally the last session covered some recent results in the area of sketching, hashing and dynamic algorithms.
Morteza Zadimoghaddam
(Google New York) opened the session describing a new algorithm for
dynamic consistent hashing
. Then
Robert Krauthgamer
(Weizmann Institute of Science) presented some
recent results on graph sketching and combinatorial optimization
.
Sayan Bhattacharya
(University of Warwick) described the design of
Dynamic Algorithms via Primal-Dual Method
. And finally
Pino Italiano
(University of Rome Tor Vergata) presented
new efficient algorithms for network analysis
.
Overall, it was a great day with many excellent talks and with many opportunities for discussing interesting problems. All the presentations, including videos, can be found on our workshop website,
here
.
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