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23. Nov. 2023 · Aaron Roth's own modesty may stand in the way of understanding the depth of his contributions. In fact, when he authored his doctoral thesis on differential privacy about 15 years ago and then wrote on the fairness of algorithms a few years later, terms like “Artificial Intelligence” and “Machine Learning” were far from being as firmly anchored in our everyday lives as they are today.
Beliebt bei Aaron K. Roth. Man kann nicht nicht kommunizieren · Berufserfahrung: Stiftung Brandenburgische Gedenkstätten · Ausbildung: Humboldt-Universität zu Berlin · Standort: Berlin · 416 Kontakte auf LinkedIn. Sehen Sie sich das Profil von Aaron K. Roth auf LinkedIn, einer professionellen Community mit mehr als 1 Milliarde Mitgliedern ...
- Stiftung Brandenburgische Gedenkstätten
Abstract The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals
Fischer & Partner. AARON BORIS ROTHE RECHTSANWALT. • Geboren 1970 in Hamburg • Studium an den Universitäten Hamburg und Münster • Berufliche Laufbahn als Rechtsanwalt und Syndikus in internationalen Medienunternehmen • div. Lehr- und Referententätigkeiten • Lehrbeauftragter Technische Hochschule Köln • Ehrenamtl. Tätigkeit ...
The ability to amass, store, manipulate and analyze information from millions of people at once has opened a vast frontier of new research methods. But, whether these methods are used in the service of new business models or new scientific findings, they also raise questions for the individuals whose information comprises these “big data” sets.
The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals becomes increasingly detailed, and as technology enables ever more powerful collection and curation of these data, the need increases for a robust, meaningful, and mathematically rigorous definition of privacy, together with a computationally rich class of ...
Foundations for Private, Fair, and Robust Data Science. Aaron Roth. Much of modern machine learning and statistics is based on the following paradigm: the algo-rithm designer specifies an objective function, and then optimizes it over some class of models. This is a powerful methodology, but while it generally results in a tool that is ...
