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Author

Chaemoon Im

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2 papers indexed here

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2026

Differentially-Private Quantum Federated Learning Against Gradient Inversion Attacks

Despite the structural advantages for privacy in federated learning (FL), many gradient inversion attacks have widely appeared to endanger the privacy of participants, by exploiting the information during communications. This is still valid for the case where FL is extended to quantum FL (QFL) to utilize quantum advant...

Chaemoon Im, Soohyun Park, Joongheon Kim · 0 citations
Preprint Sep 2026

Fourier-Geometric Circuit Design for Gate and Entanglement Placement in Quantum Neural Networks

The output of a parameterized quantum circuit (PQC) can be expressed as a finite Fourier series whose accessible frequencies are fixed by the data-encoding gates. While the encoder determines which frequencies can appear, the corresponding Fourier coefficients depend on how the trainable and entangling gates are arrang...

Seungcheol Oh, Chaemoon Im, Daeyeun Kim et al. · 1 citation

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