ELSA Newsletter - June 2023
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| ELSA Newsletter - August 2023 | |
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Dear all,
welcome to our first ELSA newsletter. We are happy to present you the news about our ELSA project in this newsletter. Take a look and find out more! |
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Last activities in the Project
| Here you can find out what has been going on in the ELSA project
over the last few months |
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ICML 2023
in Hawaii | From July 23rd to 29th, the Fortieth International Conference on Machine Learning took place in Hawaii. At the 2nd Workshop on Formal Verification of Machine Learning, four papers were honored with an Outstanding Paper Award sponsored by ELSA. |
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ELSA Workshop
in Helsinki | From March 23 to 25, experts in AI and machine learning from across Europe met in Helsinki to discuss pressing privacy issues in the use of AI applications. ELSA coordinator Mario Fritz was very pleased with the kick-off in Helsinki: "I am grateful for being able to advance the vision of ELSA together with so many great partners."
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ELSA Mobility Program | The ELSA mobility grant offers PhDs and Postdos as well as experienced researchers the opportunity to financially support their travels.
On the ELSA website, you can learn more about the program and how it supports you. |
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Looking for a new job?
| With the initiation of the network and inauguration of the virtual center of excellence in October 2022, we are offering several open positions.
Please check our network page for more detail. |
| Check this out |
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Next steps in the Project | From September 25th to 27th, 2023, the first ELSA General Assembly will take place in Sestri Levante, to which all consortium members are cordially invited. We will discuss the milestones achieved so far and plan the next steps in the project. The event is organized by UNIGE, CINI, UNICA, and PLURIBUS-ONE.
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Recently published paper
| Here you can find all recently published papers related to the ELSA project. |
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“Fair Empirical Risk Minimization Revised”
| This Paper written by Danilo Franco, Luca Oneto, and Davide Anguita addresses the issue of algorithmic fairness in machine learning. It proposes a new concept of fairness that is translated into a fairness constraint and introduces a novel convex relaxation method with stronger consistency properties. |
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"Fact-Saboteurs: A Taxonomy of Evidence Manipulation Attacks against Fact-Verification Systems" |
Mis- and disinformation pose a global threat, and automated fact-checking systems may be vulnerable to attacks. This study written by Sahar Abdelnabi and Mario Fritz explores attack methods where adversaries tamper with online evidence, degrading fact-checking performance and revealing limitations in models' inference. |
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