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This paper concerns the probabilistic evaluation of the effects of actions in the presence of unmeasured variables. We show that the identification of causal effect between a singleton variable X and a set of variables Y can be accomplished…

Artificial Intelligence · Computer Science 2013-02-21 David Galles , Judea Pearl

Identifying the effects of causes and causes of effects is vital in virtually every scientific field. Often, however, the needed probabilities may not be fully identifiable from the data sources available. This paper shows how partial…

Artificial Intelligence · Computer Science 2023-01-31 Ang Li , Scott Mueller , Judea Pearl

In probability theory, there is a tendency to treat one random variable with a given distribution as being just as good as any other. By and large this is fine because probability is (mostly) concerned with distributional properties of…

Probability · Mathematics 2013-01-31 Douglas Rizzolo

We revisit the distributed hypothesis testing (or hypothesis testing with communication constraints) problem from the viewpoint of privacy. Instead of observing the raw data directly, the transmitter observes a sanitized or randomized…

Information Theory · Computer Science 2019-06-26 Atefeh Gilani , Selma Belhadj Amor , Sadaf Salehkalaibar , Vincent Y. F. Tan

The aim of this short note is to show how can be derived from the properties of fundamental interpolation polynomials some nice identities.

History and Overview · Mathematics 2014-12-23 Sorin G. Gal

We derive uniformly most powerful (UMP) tests for simple and one-sided hypotheses for a population proportion within the framework of Differential Privacy (DP), optimizing finite sample performance. We show that in general, DP hypothesis…

Statistics Theory · Mathematics 2018-05-24 Jordan Awan , Aleksandra Slavkovic

We show that a binomial identity arising in the context of the study of series expansions of $1/\pi$ can be seen as an incarnation of Whipples second theorem for hypergeometric series.

Number Theory · Mathematics 2019-07-23 Benjamin Hackl , Helmut Prodinger

Checking two probabilistic automata for equivalence has been shown to be a key problem for efficiently establishing various behavioural and anonymity properties of probabilistic systems. In recent experiments a randomised equivalence test…

Formal Languages and Automata Theory · Computer Science 2012-01-09 Stefan Kiefer , Andrzej S. Murawski , Joël Ouaknine , Björn Wachter , James Worrell

Frequentist inference typically is described in terms of hypothetical repeated sampling but there are advantages to an interpretation that uses a single random sample. Contemporary examples are given that indicate probabilities for random…

Other Statistics · Statistics 2019-06-21 Paul Vos , Don Holbert

Motivated by the question of data quantization and "binning," we revisit the problem of identity testing of discrete probability distributions. Identity testing (a.k.a. one-sample testing), a fundamental and by now well-understood problem…

Data Structures and Algorithms · Computer Science 2020-04-28 Clément L. Canonne , Karl Wimmer

Differential privacy is among the most prominent techniques for preserving privacy of sensitive data, oweing to its robust mathematical guarantees and general applicability to a vast array of computations on data, including statistical…

Cryptography and Security · Computer Science 2021-11-25 Naoise Holohan , Stefano Braghin

We introduce a new approach to solving path-finding problems under uncertainty by representing them as probabilistic models and applying domain-independent inference algorithms to the models. This approach separates problem representation…

Artificial Intelligence · Computer Science 2015-06-09 David Tolpin , Brooks Paige , Jan Willem van de Meent , Frank Wood

For two matrices $A$ and $B$, and large $n$, we show that most products of $n$ factors of $e^{A/n}$ and $n$ factors of $e^{B/n}$ are close to $e^{A + B}$. This extends the Lie-Trotter formula. The elementary proof is based on the relation…

Combinatorics · Mathematics 2022-07-19 Michael Anshelevich , Austin Pritchett

Implementing Bayesian inference is often computationally challenging in applications involving complex models, and sometimes calculating the likelihood itself is difficult. Synthetic likelihood is one approach for carrying out inference…

Computation · Statistics 2021-03-15 David T. Frazier , David J. Nott , Christopher Drovandi , Robert Kohn

The asymptotic expansion of the distribution of the gradient test statistic is derived for a composite hypothesis under a sequence of Pitman alternative hypotheses converging to the null hypothesis at rate $n^{-1/2}$, $n$ being the sample…

Statistics Theory · Mathematics 2015-03-17 Artur Lemonte , Silvia Ferrari

We show the existence of regular combinatorial objects which previously were not known to exist. Specifically, for a wide range of the underlying parameters, we show the existence of non-trivial orthogonal arrays, t-designs, and t-wise…

Combinatorics · Mathematics 2019-09-16 Greg Kuperberg , Shachar Lovett , Ron Peled

We show the existence of rigid combinatorial objects which previously were not known to exist. Specifically, for a wide range of the underlying parameters, we show the existence of non-trivial orthogonal arrays, $t$-designs, and $t$-wise…

Combinatorics · Mathematics 2017-03-14 Greg Kuperberg , Shachar Lovett , Ron Peled

The absolute moments of probability distributions are much more complicated than conventional ones. By using a direct and simpler approach, we retreat P. L. Hsu's (1951, J. Chinese Math. Soc., Vol. 1, pp. 257-280) formulas in terms of the…

Probability · Mathematics 2019-01-01 Gwo Dong Lin , Chin-Yuan Hu

By investigating a recurrence relation about functions, we first give alternative proofs of various identities on Fibonacci numbers and Lucas numbers, and then, make certain well known identities visible via certain trivalent graph…

Number Theory · Mathematics 2013-04-04 Cheng Lien Lang , Mong Lung Lang

The field of property testing of probability distributions, or distribution testing, aims to provide fast and (most likely) correct answers to questions pertaining to specific aspects of very large datasets. In this work, we consider a…

Data Structures and Algorithms · Computer Science 2015-04-27 Clément L. Canonne
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