15 papers · 1 filter
Bounds on the privacy amplification of arbitrary channels via the contraction of -divergence
Leonhard Grosse, Sara Saeidian, Tobias J. Oechtering +1
We examine the privacy amplification of channels that do not necessarily satisfy any LDP guarantee by analyzing their contraction behavior in terms of -divergence, an -div…
Risk level dependent Minimax Quantile lower bounds for Interactive Statistical Decision Making
Raghav Bongole, Amirreza Zamani, Tobias J. Oechtering +1
Minimax risk and regret focus on expectation, missing rare failures critical in safety-critical bandits and reinforcement learning. Minimax quantiles capture these tails. Three str…
Causal Coordination for Distributed Decision-Making
Mengyuan Zhao, Tobias J. Oechtering, Maël Le Treust
In decentralized network control, communication plays a critical role by transforming local observations into shared knowledge, enabling agents to coordinate their actions. This pa…
Privacy Mechanism Design based on Empirical Distributions
Leonhard Grosse, Sara Saeidian, Mikael Skoglund +1
Pointwise maximal leakage (PML) is a per-outcome privacy measure based on threat models from quantitative information flow. Privacy guarantees with PML rely on knowledge about the…
Low-Power Optimal Strategy for Witsenhausen Counterexample
Mengyuan Zhao, Maël Le Treust, Tobias J. Oechtering
We discuss the Witsenhausen counterexample from the perspective of varying power budgets and propose a low-power estimation (LoPE) strategy. Specifically, our LoPE approach designs…
A Tight Context-aware Privacy Bound for Histogram Publication
Sara Saeidian, Ata Yavuzyılmaz, Leonhard Grosse +2
We analyze the privacy guarantees of the Laplace mechanism releasing the histogram of a dataset through the lens of pointwise maximal leakage (PML). While differential privacy is c…