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Lower bounds and impossibility results in distributed computing are both intellectually challenging and practically important. Hundreds if not thousands of proofs appear in the literature, but surprisingly, the vast majority of them apply…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-10-13 Guy Goren , Yoram Moses , Alexander Spiegelman

The standard definition formula for probabilities of independent events is derived as a consequence of the Insufficient Reason Principle expressed as the Maximum Relative Divergence Principle for grading (order-comonotonic) functions on a…

Probability · Mathematics 2025-08-05 Alexander Dukhovny

Inferential models (IMs) are data-dependent, imprecise-probabilistic structures designed to quantify uncertainty about unknowns. As the name suggests, the focus has been on uncertainty quantification for inference and on its reliability…

Statistics Theory · Mathematics 2026-05-01 Ryan Martin , Shih-Ni Prim , Jonathan Williams

We define cryptographic assumptions applicable to two mistrustful parties who each control two or more separate secure sites between which special relativity guarantees a time lapse in communication. We show that, under these assumptions,…

Quantum Physics · Physics 2009-10-31 Adrian Kent

There had been well known claims of ``provably unbreakable'' quantum protocols for bit commitment and coin tossing. However, we, and independently Mayers, showed that all proposed quantum bit commitment (and therefore coin tossing) schemes…

Quantum Physics · Physics 2008-02-03 Hoi-Kwong Lo , H. F. Chau

Predicting the future is an important component of decision making. In most situations, however, there is not enough information to make accurate predictions. In this paper, we develop a theory of causal reasoning for predictive inference…

Artificial Intelligence · Computer Science 2013-04-10 Thomas L. Dean , Keiji Kanazawa

In this paper, we study the notion of admissibility for randomised strategies in concurrent games. Intuitively, an admissible strategy is one where the player plays `as well as possible', because there is no other strategy that dominates…

Computer Science and Game Theory · Computer Science 2017-02-22 Nicolas Basset , Gilles Geeraerts , Jean-François Raskin , Ocan Sankur

Given a universe of discourse X-a domain of possible outcomes-an experiment may consist of selecting one of its elements, subject to the operation of chance, or of observing the elements, subject to imprecision. A priori uncertainty about…

Artificial Intelligence · Computer Science 2013-03-26 Arthur Ramer

The Improbability Scale (IS) is proposed as a way of communicating to the general public the improbability (and by implication, the probability) of events predicted as the result of scientific research. Through the use of the Improbability…

Physics and Society · Physics 2007-05-23 David J. Ritchie

The Born's rule introduces intrinsic randomness to the outcomes of a measurement performed on a quantum mechanical system. But, if the system is prepared in the eigenstate of an observable then the measurement outcome of that observable is…

Quantum Physics · Physics 2014-03-31 Trina Chakraborty , Manik Banik , Pinaki Patra

There had been well known claims of unconditionally secure quantum protocols for bit commitment. However, we, and independently Mayers, showed that all proposed quantum bit commitment schemes are, in principle, insecure because the sender,…

Quantum Physics · Physics 2009-10-30 H. -K. Lo , H. F. Chau

Lottery is a game in which multiple players take chances in the hope of getting some rewards in cash or kind. In addition, from the time of the early civilizations, lottery has also been considered as an apposite method to allocate scarce…

Quantum Physics · Physics 2022-03-24 Sandeep Mishra , Anirban Pathak

We introduce a "high probability" framework for repeated games with incomplete information. In our non-equilibrium setting, players aim to guarantee a certain payoff with high probability, rather than in expected value. We provide a high…

Computer Science and Game Theory · Computer Science 2015-09-30 Payam Delgosha , Amin Gohari , Mohammad Akbarpour

A decision maker starts from a judgmental decision and moves to the closest boundary of the confidence interval. This statistical decision rule is admissible and does not perform worse than the judgmental decision with a probability equal…

Methodology · Statistics 2019-03-19 Simone Manganelli

The uncertainty principle can be understood as constraining the probability of winning a game in which Alice measures one of two conjugate observables, such as position or momentum, on a system provided by Bob, and he is to guess the…

Quantum Physics · Physics 2017-07-06 Joseph M. Renes

This contribution derives from a rather extensive study on the foundations of probability. We start by discussing critically the two main models of the random event in Probability Theroy and cast light over a number of incongruities. We…

Probability · Mathematics 2007-05-23 Paolo Rocchi , Leonida Gianfagna

Motivated by applications to goodness of fit testing, the empirical likelihood approach is generalized to allow for the number of constraints to grow with the sample size and for the constraints to use estimated criteria functions. The…

Statistics Theory · Mathematics 2013-07-24 Hanxiang Peng , Anton Schick

We present different versions of a conjecture which would express that first price mechanisms never work very badly in a very general class of problems. The definitions include most of the problems where there is a principal (seller) who…

Economics · Quantitative Finance 2015-09-01 Endre Csóka

In the distrustful quantum cryptography model the different parties have conflicting interests and do not trust one another. Nevertheless, they trust the quantum devices in their labs. The aim of the device-independent approach to…

Quantum Physics · Physics 2011-06-10 J. Silman , A. Chailloux , N. Aharon , I. Kerenidis , S. Pironio , S. Massar

Statistical machine learning theory often tries to give generalization guarantees of machine learning models. Those models naturally underlie some fluctuation, as they are based on a data sample. If we were unlucky, and gathered a sample…

Machine Learning · Computer Science 2022-11-21 Alexander Mey