*Abstract*
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13Mar
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13Mar
*Abstract*
*Bio*Stay Tuned!
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17Mar
Current privacy evaluations in machine learning (ML) rely predominantly on membership inference attacks to validate claims of differential privacy and machine unlearning. By framing ML regulation as a Principal-Agent problem, we demonstrate that regulators cannot rely on such attacks alone due to information asymmetry.
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18Mar
Abstract not available
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19Mar
Abstract not available
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20Mar
Abstract not available
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20Mar
*Abstract*
Stay Tuned!
*Bio*
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23Mar
Users’ subjective experience of a technology’s transparency plays a pivotal role in human-computer interaction, shaping trust, satisfaction, and technology use.
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24Mar
Note the room change to room FW26.
This paper is published in Quantum at https://quantum-journal.org/papers/q-2025-07-03-1786/
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26Mar
When designing complex systems, we need to consider multiple trade-offs at various abstraction levels and scales, and choices of single components need to be studied jointly.
