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In this paper we consider the inference rules of System P in the framework of coherent imprecise probabilistic assessments. Exploiting our algorithms, we propagate the lower and upper probability bounds associated with the conditional…

Probability · Mathematics 2007-05-23 Angelo Gilio

This paper develops upper and lower bounds for the probability of Boolean functions by treating multiple occurrences of variables as independent and assigning them new individual probabilities. We call this approach dissociation and give an…

Artificial Intelligence · Computer Science 2015-06-30 Wolfgang Gatterbauer , Dan Suciu

In this paper, I present a completely new type of upper and lower bounds on the right-tail probabilities of continuous random variables with unbounded support and with semi-bounded support from the left. The presented upper and lower…

Probability · Mathematics 2023-11-28 Nikola Zlatanov

There are many ways of establishing upper bounds on fluctuations of random variables, but there is no systematic approach for lower bounds. As a result, lower bounds are unknown in many important problems. This paper introduces a general…

Probability · Mathematics 2018-07-30 Sourav Chatterjee

Probabilistic Logic Programming is an effective formalism for encoding problems characterized by uncertainty. Some of these problems may require the optimization of probability values subject to constraints among probability distributions…

Logic in Computer Science · Computer Science 2023-06-22 Damiano Azzolini , Fabrizio Riguzzi

We derive sharp probability bounds on the tails of a product of symmetric non-negative random variables using only information about their first two moments. If the covariance matrix of the random variables is known exactly, these bounds…

Probability · Mathematics 2016-05-19 Napat Rujeerapaiboon , Daniel Kuhn , Wolfram Wiesemann

For arbitrary two probability measures on real d-space with given means and variances (covariance matrices), we provide lower bounds for their total variation distance. In the one-dimensional case, a tight bound is given.

Probability · Mathematics 2022-12-27 Tomohiro Nishiyama

The existence of a pivot rule for the simplex method that guarantees a strongly polynomial run-time is a longstanding, fundamental open problem in the theory of linear programming. The leading pivot rule in theory is the shadow pivot rule,…

Optimization and Control · Mathematics 2024-05-09 Alexander E. Black

Coherent lower previsions are general probabilistic models allowing incompletely specified probability distributions. However, for complete description of a coherent lower prevision -- even on finite underlying sample spaces -- an infinite…

Probability · Mathematics 2022-09-29 Damjan Škulj

We present a technique to infer lower bounds on the worst-case runtime complexity of integer programs, where in contrast to earlier work, our approach is not restricted to tail-recursion. Our technique constructs symbolic representations of…

Logic in Computer Science · Computer Science 2020-09-29 Florian Frohn , Matthias Naaf , Marc Brockschmidt , Jürgen Giesl

We derive new upper and lower bounds for probabilities that $r$ or at least $r$ from $n$ events occur. These bounds can turn to equalities. The method is discussed as well. It works for measurable space and measures with sign, too. We also…

Probability · Mathematics 2020-08-12 Andrei N. Frolov

Consider the boundary case in a one-dimensional super-critical branching random walk. It is known that upon the survival of the system, the minimal position after $n$ steps behaves in probability like ${3\over 2} \log n$ when $n\to \infty$.…

Probability · Mathematics 2011-02-02 Elie Aidekon , Zhan Shi

In Part II we show that there exist quantum codes whose probability of undetected error falls exponentially with the length of the code and derive bounds on this exponent.The lower (existence) bound for stabilizer codes is proved by a…

Quantum Physics · Physics 2007-05-23 A. Ashikhmin , A. Barg , E. Knill , S. Litsyn

Computing the reachability probability in infinite state probabilistic models has been the topic of numerous works. Here we introduce a new property called \emph{divergence} that when satisfied allows to compute reachability probabilities…

Formal Languages and Automata Theory · Computer Science 2026-03-03 Alain Finkel , Serge Haddad , Lina Ye

Distributionally robust chance constrained programs minimize a deterministic cost function subject to the satisfaction of one or more safety conditions with high probability, given that the probability distribution of the uncertain problem…

Optimization and Control · Mathematics 2022-11-22 Zhi Chen , Daniel Kuhn , Wolfram Wiesemann

Let $M_n$ be the minimal position at generation $n$, of a real-valued branching random walk in the boundary case. As $n \to \infty$, $M_n- {3 \over 2} \log n$ is tight (see [1][9][2]). We establish here a law of iterated logarithm for the…

Probability · Mathematics 2017-07-06 Yueyun Hu

A risk-aware decision-making problem can be formulated as a chance-constrained linear program in probability measure space. Chance-constrained linear program in probability measure space is intractable, and no numerical method exists to…

Optimization and Control · Mathematics 2023-11-21 Xun Shen , Satoshi Ito

We study discrete probabilistic programs with potentially unbounded looping behaviors over an infinite state space. We present, to the best of our knowledge, the first decidability result for the problem of determining whether such a…

Logic in Computer Science · Computer Science 2022-06-22 Mingshuai Chen , Joost-Pieter Katoen , Lutz Klinkenberg , Tobias Winkler

This article investigates the behavior of the continuous-time simple random walk on $\mathbb{Z}^d$, $d \geq 3$. We derive an asymptotic lower bound on the principal exponential rate of decay for the probability that the average value over a…

Probability · Mathematics 2025-07-24 Alberto Chiarini , Maximilian Nitzschner

We develop a new technique for proving distribution testing lower bounds for properties defined by inequalities involving the bin probabilities of the distribution in question. Using this technique we obtain new lower bounds for…

Machine Learning · Computer Science 2023-08-02 Yuqian Cheng , Daniel M. Kane , Zhicheng Zheng