331 citations · 712 across the 75 of their papers we have counts for
83 papers
Contraction and Statistical Inference under Privacy for Uniformly Bounded Distributions
Leonhard Grosse, Sara Saeidian, Tobias J. Oechtering +1
We investigate -interior pointwise maximal leakage (PML) as a tool for contraction analyses and disclosure control. Based on the strong adversarial threat models from maximal le…
Trust-Aware Adaptive Disclosure for Inference Privacy Preservation in Multi-Agent Networks
Puspanjali Ghoshal, Tobias J. Oechtering
Agent based systems are increasingly deployed in information critical systems including healthcare management systems, and smart grids. In this paper, we consider a multi-agent sys…
Minimax Quantile Lower Bounds for Interactive Statistical Decision Making with Privacy
Raghav Bongole, Amirreza Zamani, Tobias J. Oechtering +1
Minimax risk and regret are expectation-based criteria and do not capture rare but consequential failures. To address this concern, we develop a -explicit minimax-quantile theor…
Worst-Case Utility Privacy Mechanism via Pointwise Maximal Leakage
Ci Song, Tobias J. Oechtering
We propose a discrete privacy mechanism exploiting beneficial properties of the novel privacy measure Pointwise Maximal Leakage (PML). Given the utility assignment characterized by…
Instantiating Bayesian CVaR lower bounds in Interactive Decision Making Problems
Raghav Bongole, Tobias J. Oechtering, Mikael Skoglund
Recent work established a generalized-Fano framework for lower bounding prior-predictive (Bayesian) CVaR in interactive statistical decision making. In this paper, we show how to i…
Generalizing the Fano inequality further
Raghav Bongole, Tobias J. Oechtering, Mikael Skoglund
Interactive statistical decision making (ISDM) features algorithm-dependent data generated through interaction. Existing information-theoretic lower bounds in ISDM largely target e…