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AMDROMA SIGNED

Algorithmic and Mechanism Design Research in Online MArkets

Total Cost €

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EC-Contrib. €

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Partnership

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Project "AMDROMA" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITA DEGLI STUDI DI ROMA LA SAPIENZA 

Organization address
address: Piazzale Aldo Moro 5
city: ROMA
postcode: 185
website: www.uniroma1.it

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Italy [IT]
 Project website http://www.diag.uniroma1.it/ERCAMDROMA
 Total cost 1˙780˙150 €
 EC max contribution 1˙780˙150 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2017-ADG
 Funding Scheme ERC-ADG
 Starting year 2018
 Duration (year-month-day) from 2018-07-01   to  2023-06-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITA DEGLI STUDI DI ROMA LA SAPIENZA IT (ROMA) coordinator 1˙780˙150.00

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 Project objective

Online markets currently form an important share of the global economy. The Internet hosts classical markets (real-estate, stocks, e-commerce) as well allowing new markets with previously unknown features (web-based advertisement, viral marketing, digital goods, crowdsourcing, sharing economy). Algorithms play a central role in many decision processes involved in online markets. For example, algorithms run electronic auctions, trade stocks, adjusts prices dynamically, and harvest big data to provide economic information. Thus, it is of paramount importance to understand the algorithmic and mechanism design foundations of online markets.

The algorithmic research issues that we consider involve algorithmic mechanism design, online and approximation algorithms, modelling uncertainty in online market design, and large-scale data analysisonline and approximation algorithms, large-scale optimization and data mining. The aim of this research project is to combine these fields to consider research questions that are central for today's Internet economy. We plan to apply these techniques so as to solve fundamental algorithmic problems motivated by web-basedInternet advertisement, Internet market designsharing economy, and crowdsourcingonline labour marketplaces. While my planned research is focussedcentered on foundational work with rigorous design and analysis of in algorithms and mechanismsic design and analysis, it will also include as an important component empirical validation on large-scale real-life datasets.

 Publications

year authors and title journal last update
List of publications.
2020 Matteo Bohm, Adriano Fazzone, Stefano Leonardi, Chris Schwiegelshohn
Fair Clustering with Multiple Colors
published pages: , ISSN: , DOI:
CoRR 2020-03-05
2020 Paul Dutting, Federico Fusco, Philip Lazos, Stefano Leonardi, Rebecca Reiffenhauser
Efficient Two-Sided Markets with Limited Information
published pages: , ISSN: , DOI:
CoRR 2020-03-05
2020 Georgios Amanatidis, Georgios Birmpas, Aris Filos-Ratsikas, Alexandros Hollender, Alexandros A. Voudouris
Maximum Nash Welfare and Other Stories About EFX
published pages: , ISSN: , DOI:
CoRR 2020-03-05
2020 Shant Boodaghians, Federico Fusco, Philip Lazos, Stefano Leonardi
Pandora\'s Box Problem with Order Constraints
published pages: , ISSN: , DOI:
CoRR 2020-02-20
2020 Georgios Amanatidis, Georgios Birmpas, Aris Filos-Ratsikas, Alexandros Voudouris
Peeking Behind the Ordinal Curtain: Improving Distortion via Cardinal Queries
published pages: , ISSN: , DOI:
AAAI 2020 2020-02-05
2019 Marc Bury, Elena Grigorescu, Andrew McGregor, Morteza Monemizadeh, Chris Schwiegelshohn, Sofya Vorotnikova, Samson Zhou
Structural Results on Matching Estimation with Applications to Streaming
published pages: 367-392, ISSN: 0178-4617, DOI: 10.1007/s00453-018-0449-y
Algorithmica 81/1 2019-10-28
2019 George Christodoulou, Stefano Leonardi, Alkmini Sgouritsa
Designing Cost-Sharing Methods for Bayesian Games
published pages: 4-25, ISSN: 1432-4350, DOI: 10.1007/s00224-017-9832-3
Theory of Computing Systems 63/1 2019-10-28
2019 Chris Schwiegelshohn, Uwe Schwiegelshohn
Maximizing Online Utilization with Commitment
published pages: , ISSN: , DOI:
CoRR 2019-10-28
2019 Aris Anagnostopoulos, Luca Becchetti, Matteo Böhm, Adriano Fazzone, Stefano Leonardi, Cristina Menghini and Chris Schwiegelshohn
Principal Fairness: Removing Bias via Projections
published pages: , ISSN: , DOI:
CoRR 2019-10-28
2019 Vincent Cohen-Addad, Niklas Hjuler, Nikos Parotsidis, David Saulpic, Chris Schwiegelshohn
Fully Dynamic Consistent Facility Location
published pages: , ISSN: , DOI:
NeurIPS 2019 2019-10-28
2019 Shant Boodaghians, Federico Fusco, Stefano Leonardi, Yishay Mansour and Ruta Mehta
Online Revenue Maximization for Server Pricing
published pages: , ISSN: , DOI:
2019-10-28
2019 Melanie Schmidt, Chris Schwiegelshohn, Christian Sohler
Fair Coresets and Streaming Algorithms for Fair k-Means Clustering
published pages: , ISSN: , DOI:
WAOA 2019-10-28
2019 Riccardo Colini-Baldeschi, Stefano Leonardi, Okke Schrijvers and Eric Sodomka
Envy, Regret, and Social Welfare Loss
published pages: , ISSN: , DOI:
2019-10-28
2019 Marc Bury, Chris Schwiegelshohn, Mara Sorella
Similarity Search for Dynamic Data Streams
published pages: 1-1, ISSN: 1041-4347, DOI: 10.1109/tkde.2019.2916858
IEEE Transactions on Knowledge and Data Engineering 2019-10-28
2018 Alexander Munteanu, Chris Schwiegelshohn, Christian Sohler, David Woodruff
On Coresets for Logistic Regression
published pages: 6561--6570, ISSN: , DOI:
Advances in Neural Information Processing Systems 31 2019-10-28

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