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In quantitative information flow we say that program $Q$ is "at least as secure as" $P$ just when the amount of secret information flowing from $Q$ is never more than flows from $P$, with of course a suitable quantification of "flow". This…

Cryptography and Security · Computer Science 2016-04-19 N. Bordenabe , A. McIver , C Morgan , T. Rabehaja

The quantification of aleatoric and epistemic uncertainty in terms of conditional entropy and mutual information, respectively, has recently become quite common in machine learning. While the properties of these measures, which are rooted…

Machine Learning · Computer Science 2023-06-27 Lisa Wimmer , Yusuf Sale , Paul Hofman , Bern Bischl , Eyke Hüllermeier

A compression function is a map that slims down an observational set into a subset of reduced size, while preserving its informational content. In multiple applications, the condition that one new observation makes the compressed set change…

Machine Learning · Computer Science 2024-01-09 Marco C. Campi , Simone Garatti

Probabilistic separation logic offers an approach to reasoning about imperative probabilistic programs in which a separating conjunction is used as a mechanism for expressing independence properties. Crucial to the effectiveness of the…

Logic in Computer Science · Computer Science 2026-03-03 Janez Ignacij Jereb , Alex Simpson

The problem of reliable function computation is extended by imposing privacy, secrecy, and storage constraints on a remote source whose noisy measurements are observed by multiple parties. The main additions to the classic function…

Information Theory · Computer Science 2023-07-19 Onur Günlü

Accurate quantification of model uncertainty has long been recognized as a fundamental requirement for trusted AI. In regression tasks, uncertainty is typically quantified using prediction intervals calibrated to a specific operating point,…

Machine Learning · Computer Science 2021-06-03 Jiri Navratil , Benjamin Elder , Matthew Arnold , Soumya Ghosh , Prasanna Sattigeri

In this paper we argue that, to its detriment, transparency research overlooks many foundational concepts of artificial intelligence. As an illustrating example we focus on uncertainty quantification in the context of counterfactual…

Machine Learning · Computer Science 2026-05-19 Kacper Sokol , Santo M. A. R. Thies , Eyke Hüllermeier

Percolation is an emblematic model to assess the robustness of interconnected systems when some of their components are corrupted. It is usually investigated in simple scenarios, such as the removal of the system's units in random order, or…

Statistical Mechanics · Physics 2021-05-03 Oriol Artime , Manlio De Domenico

We examine the relationship between privacy metrics that utilize information density to measure information leakage between a private and a disclosed random variable. Firstly, we prove that bounding the information density from above or…

Information Theory · Computer Science 2024-02-21 Leonhard Grosse , Sara Saeidian , Parastoo Sadeghi , Tobias J. Oechtering , Mikael Skoglund

Incompatibility of certain measurements -- impossibility of obtaining deterministic outcomes simultaneously -- is a well known property of quantum mechanics. This feature can be utilized in many contexts, ranging from Bell inequalities to…

Quantum Physics · Physics 2018-03-14 Martin Plesch , Matej Pivoluska

Probabilistic partial observability is a phenomenon occuring when computer systems are deployed in environments that behave probabilistically and whose exact state cannot be fully observed. In this work, we lay the theoretical groundwork…

Logic in Computer Science · Computer Science 2025-06-17 Tobias Gürtler , Benjamin Lucien Kaminski

We propose an operational measure of information leakage in a non-stochastic setting to formalize privacy against a brute-force guessing adversary. We use uncertain variables, non-probabilistic counterparts of random variables, to construct…

Information Theory · Computer Science 2021-01-29 Farhad Farokhi , Ni Ding

The main result presented in this article is that probability can fundamentally be characterized as a subset of conditional expectation induced by a plausible preorder on random quantities. This is justified by the fact that probability is…

Logic · Mathematics 2024-06-14 Ladislav Mečíř

We propose an information-theoretic quantifier for the advantage gained from cooperation that captures the degree of dependency between subsystems of a global system. The quantifier is distinct from measures of multipartite correlations…

Quantitative theories of information flow give us an approach to relax the absolute confidentiality properties that are difficult to satisfy for many practical programs. The classical information-theoretic approaches for sequential…

Cryptography and Security · Computer Science 2013-06-13 Tri Minh Ngo , Marieke Huisman

We provide a framework for reasoning about information-hiding requirements in multiagent systems and for reasoning about anonymity in particular. Our framework employs the modal logic of knowledge within the context of the runs and systems…

Cryptography and Security · Computer Science 2007-05-23 Joseph Y. Halpern , Kevin R. O'Neill

A program is non-interferent if it leaks no secret information to an observable output. However, non-interference is too strict in many practical cases and quantitative information flow (QIF) has been proposed and studied in depth.…

Cryptography and Security · Computer Science 2019-10-23 Bao Trung Chu , Kenji Hashimoto , Hiroyuki Seki

Invisibility cloaking in acoustic scattering via the approach of transformation optics is considered. The near-cloaks of both passive medium and active/radiating object are investigated. From a practical viewpoint, we are especially…

Analysis of PDEs · Mathematics 2012-11-12 Hongyu Liu

On the basis of the general character and operation of the process of perception, a formalism is sought to mathematically describe the subjective or abstract/mental process of perception. It is shown that the formalism of orthodox quantum…

Neurons and Cognition · Quantitative Biology 2009-10-13 Efstratios Manousakis

The lack of information obtained from informationally incomplete quantum measurements can prevent the detection of quantum resources, such as optical nonclassicality. We develop a technique that overcomes this limitation for single-mode…

Quantum Physics · Physics 2025-05-07 V. S. Kovtoniuk , A. B. Klimov , A. A. Semenov