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In dealing with asymptotic approximation of possibly divergent nets of probability distributions, we are led to study uniform structures on the set of distributions. This paper identifies a class of such uniform structures that may be…

Probability · Mathematics 2010-11-23 Jan Pachl

We study trade-off relations in information extraction from quantum systems subject to null-result weak measurements, where the absence of a detected photon continuously updates the system state. We present a detailed analysis of qubit and…

Quantum Physics · Physics 2026-05-15 Luis D. Zambrano Palma , Yusef Maleki , M. Suhail Zubairy

As wireless has disrupted communications, wireless will also disrupt the delivery of energy. Future wireless networks will be equipped with (radiative) wireless power transfer (WPT) capability and exploit radio waves to carry both energy…

Information Theory · Computer Science 2022-09-09 Bruno Clerckx , Junghoon Kim , Kae Won Choi , Dong In Kim

We introduce a hierarchical classification of theories that describe systems with fundamentally limited information content. This property is introduced in an operational way and gives rise to the existence of mutually complementary…

Quantum Physics · Physics 2010-05-27 Tomasz Paterek , Borivoje Dakic , Caslav Brukner

Generalizing empirical findings to new environments, settings, or populations is essential in most scientific explorations. This article treats a particular problem of generalizability, called "transportability", defined as a license to…

Artificial Intelligence · Computer Science 2014-01-03 Elias Bareinboim , Judea Pearl

Does information play a significant role in the foundations of physics? Information is the abstraction that allows us to refer to the states of systems when we choose to ignore the systems themselves. This is only possible in very…

Quantum Physics · Physics 2014-03-05 Lluis Masanes , Markus P. Mueller , Remigiusz Augusiak , David Perez-Garcia

Probabilistic inference problems arise naturally in distributed systems such as sensor networks and teams of mobile robots. Inference algorithms that use message passing are a natural fit for distributed systems, but they must be robust to…

Artificial Intelligence · Computer Science 2012-07-19 Mark Paskin , Carlos E. Guestrin

This work provides some general theorems about unconditional and conditional weak convergence of empirical processes in the case of Poisson sampling designs. The theorems presented in this work are stronger than previously published…

Statistics Theory · Mathematics 2019-06-12 Leo Pasquazzi

We develop a diffusion approximation for systems subject to fast random resetting by small amplitudes. Equivalently, this describes systems with frequent but small catastrophes. We demonstrate the validity of the approximation by computing…

Statistical Mechanics · Physics 2026-02-26 Tobias Galla

We prove that any two general probabilistic theories (GPTs) are entangleable, in the sense that their composite exhibits either entangled states or entangled measurements, if and only if they are both non-classical, meaning that neither of…

Quantum Physics · Physics 2022-05-02 Guillaume Aubrun , Ludovico Lami , Carlos Palazuelos , Martin Plávala

Predicting the evolution of a large system of units using its structure of interaction is a fundamental problem in complex system theory. And so is the problem of reconstructing the structure of interaction from temporal observations. Here,…

Statistical Mechanics · Physics 2025-02-10 Charles Murphy , Vincent Thibeault , Antoine Allard , Patrick Desrosiers

This paper is devoted to the study of the separability problem in the field of Quantum information theory. We deal mainly with the bipartite finite dimensional case and with two types of matrices, one of them being the PPT matrices. We…

Quantum Physics · Physics 2016-03-21 Daniel Cariello

Training models that perform well under distribution shifts is a central challenge in machine learning. In this paper, we introduce a modeling framework where, in addition to training data, we have partial structural knowledge of the…

Machine Learning · Computer Science 2021-10-28 Tobias Sutter , Andreas Krause , Daniel Kuhn

Foundational work on the Lottery Ticket Hypothesis has suggested an exciting corollary: winning tickets found in the context of one task can be transferred to similar tasks, possibly even across different architectures. This has generated…

Machine Learning · Computer Science 2022-07-28 William T. Redman , Tianlong Chen , Zhangyang Wang , Akshunna S. Dogra

Cooperation information sharing is important to theories of human learning and has potential implications for machine learning. Prior work derived conditions for achieving optimal Cooperative Inference given strong, relatively restrictive…

Machine Learning · Computer Science 2019-02-15 Pei Wang , Pushpi Paranamana , Patrick Shafto

One of the strengths of quantum information theory is that it can treat quantum states without referring to their particular physical representation. In principle, quantum states can be therefore fully swapped between various quantum…

Several tasks in information retrieval (IR) rely on assumptions regarding the distribution of some property (such as term frequency) in the data being processed. This thesis argues that such distributional assumptions can lead to incorrect…

Information Retrieval · Computer Science 2019-04-02 Casper Petersen

The necessary information for specifying a complex system may not be completely accessible to us, i.e., to mathematical treatments. This is not to be confounded with the incompleteness of our knowledge about whatever systems or nature,…

Statistical Mechanics · Physics 2007-05-23 Qiuping A. Wang

We investigate probabilistic transformations of quantum states from a `source' set to a `target' set of states. Such transforms have many applications. They can be used for tasks which include state-dependent cloning or quantum state…

Quantum Physics · Physics 2015-06-05 Vedran Dunjko , Erika Andersson

Wireless power transfer (WPT) technologies are becoming ubiquitous, but unlike wire technologies, they do not allow efficient energy transfer through barely transparent barriers. The proposed solutions to this issue rely on resonantly…

Optics · Physics 2019-09-16 Alex Krasnok