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20162026
most cited-Anonymity in Practice: How Generalisation and Suppression Affect Machine Learning Classifiers

62 citations · 242 across the 29 of their papers we have counts for

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Showing 2021Show all

7 papers · 1 filter

math.LO2021★ 2 cited

Continuum Many Different Things: Localisation, Anti-Localisation and Yorioka Ideals

Miguel Antonio Cardona, Lukas Daniel Klausner, Diego Alejandro Mejía

Combining creature forcing approaches from arXiv:1003.3425 and arXiv:1402.0367, we show that, under CH, there is a proper -bounding poset with -cc that forces contin…

cs.CY2021★ 25 cited

"Computer Says No": Algorithmic Decision Support and Organisational Responsibility

Angelika Adensamer, Rita Gsenger, Lukas Daniel Klausner

Algorithmic decision support is increasingly used in a whole array of different contexts and structures in various areas of society, influencing many people's lives. Its use raises…

cs.LG2021★ 25 cited

Towards Resilient Artificial Intelligence: Survey and Research Issues

Oliver Eigner, Sebastian Eresheim, Peter Kieseberg +6

Artificial intelligence (AI) systems are becoming critical components of today's IT landscapes. Their resilience against attacks and other environmental influences needs to be ensu…

cs.CY2021★ 59 cited

"Part Man, Part Machine, All Cop": Automation in Policing

Angelika Adensamer, Lukas Daniel Klausner

Digitisation, automation and datafication permeate policing and justice more and more each year -- from predictive policing methods through recidivism prediction to automated biome…

cs.CY2021★ 1 cited

Trust Me If You Can: Trusted Transformation Between (JSON) Schemas to Support Global Authentication of Education Credentials

Stefan More, Peter Grassberger, Felix Hörandner +2

Recruiters and institutions around the world struggle with the verification of diplomas issued in a diverse and global education setting. Firstly, it is a nontrivial problem to ide…

cs.LG2021★ 62 cited

-Anonymity in Practice: How Generalisation and Suppression Affect Machine Learning Classifiers

Djordje Slijepčević, Maximilian Henzl, Lukas Daniel Klausner +3

The protection of private information is a crucial issue in data-driven research and business contexts. Typically, techniques like anonymisation or (selective) deletion are introdu…

cs.LG2021

Anomaly Detection Support Using Process Classification

Sebastian Eresheim, Lukas Daniel Klausner, Patrick Kochberger

Anomaly detection systems need to consider a lot of information when scanning for anomalies. One example is the context of the process in which an anomaly might occur, because anom…