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20232026
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cs.IT2026

Exact Privacy--Distortion Design of Support-Constrained Randomized Response

Amirreza Zamani, Parastoo Sadeghi, Mikael Skoglund

Full-support local randomizers can incur unnecessary reporting distortion on ordered alphabets. We study randomized response whose output is restricted to a radius- neighborhood…

cs.IT2026

Residual-Information Generalization Bounds Under Selective Privacy: Extended Version

Amirreza Zamani, Parastoo Sadeghi, Mikael Skoglund

Information-theoretic generalization bounds usually control dependence on the task sample, whereas selective privacy may constrain only a different, private coordinate. We study i.…

cs.IT2026

Sparse Kernel Mechanisms for Locally Differentially Private Discrete Channels

Amirreza Zamani, Parastoo Sadeghi, Mikael Skoglund

We study sparse locally private discrete mechanisms generated by a nonnegative kernel and an input-dependent admissible output support. The support set is intentionally small relat…

cs.IT2026

Sparse Point-wise Privacy Leakage: Mechanism Design and Fundamental Limits

Amirreza Zamani, Sajad Daei, Parastoo Sadeghi +1

We study an information-theoretic privacy mechanism design problem, where an agent observes useful data that is arbitrarily correlated with sensitive data , and design discl…

cs.IT2026

Privacy-Utility Trade-offs Under Multi-Level Point-Wise Leakage Constraints

Amirreza Zamani, Parastoo Sadeghi, Mikael Skoglund

An information-theoretic privacy mechanism design is studied, where an agent observes useful data which is correlated with the private data . The agent wants to reveal the i…