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We give a large sieve type inequality for functions supported on primes. As application we prove a conjecture by Elliott, and give bounds for short character sums over primes. The proves uses a combination of the large sieve and the Selberg…

Number Theory · Mathematics 2011-05-10 Jan-Christoph Schlage-Puchta

Split sample methods have recently been put forward as a way to reduce the coverage oscillations that haunt confidence intervals for parameters of lattice distributions, such as the binomial and Poisson distributions. We study split sample…

Methodology · Statistics 2015-03-11 Måns Thulin

We prove an analogue of the Prime Number Theorem for short intervals on a smooth projective geometrically irreducible curve of arbitrary genus over a finite field. A short interval "of size E" in this setting is any additive translate of…

Number Theory · Mathematics 2018-04-03 Efrat Bank , Tyler Foster

We give a finite-sample analysis of predictive inference procedures after model selection in regression with random design. The analysis is focused on a statistically challenging scenario where the number of potentially important…

Statistics Theory · Mathematics 2009-08-26 Hannes Leeb

Using recent results from the theory of integer points close to smooth curves, we give an asymptotic formula for the distribution of values of a class of integer-valued prime-independent multiplicative functions.

Number Theory · Mathematics 2016-09-12 Olivier Bordellès

We study certain aspects of the Selberg sieve, in particular when sifting by rather thin sets of primes. We derive new results for the lower bound sieve suited especially for this setup and we apply them in particular to give a new…

Number Theory · Mathematics 2022-06-08 John Friedlander , Henryk Iwaniec

Motivated by algorithmic problems from combinatorial group theory we study computational properties of integers equipped with binary operations +, -, z = x 2^y, z = x 2^{-y} (the former two are partial) and predicates < and =. Notice that…

Group Theory · Mathematics 2010-06-15 Alexei G. Myasnikov , Alexander Ushakov , Dong Wook Won

We study prediction-powered conditional inference in the setting where labeled data are scarce, unlabeled covariates are abundant, and a black-box machine-learning predictor is available. The goal is to perform statistical inference on…

Machine Learning · Statistics 2026-03-09 Yang Sui , Jin Zhou , Hua Zhou , Xiaowu Dai

This paper revisits the simple, but empirically salient, problem of inference on a real-valued parameter that is partially identified through upper and lower bounds with asymptotically normal estimators. A simple confidence interval is…

Econometrics · Economics 2021-01-01 Jörg Stoye

In [10] the third author of this paper presented two conjectures on the additive decomposability of the sequence of ''smooth'' (or ''friable'') numbers. Elsholtz and Harper [4] proved (by using sieve methods) the second (less demanding)…

Number Theory · Mathematics 2020-06-30 K. Győry , L. Hajdu , A. Sárközy

In causal inference, we can consider a situation in which treatment on one unit affects others, i.e., interference exists. In the presence of interference, we cannot perform a classical randomization test directly because a null hypothesis…

Methodology · Statistics 2022-03-22 Mizuho Yanagi , Tomonari Sei

Refining one's hypotheses in the light of data is a common scientific practice; however, the dependency on the data introduces selection bias and can lead to specious statistical analysis. An approach for addressing this is via conditioning…

Machine Learning · Computer Science 2020-03-03 Jen Ning Lim , Makoto Yamada , Wittawat Jitkrittum , Yoshikazu Terada , Shigeyuki Matsui , Hidetoshi Shimodaira

We investigate algebraic and arithmetic properties of a class of sequences of sparse polynomials that have binomial coefficients both as exponents and as coefficients. In addition to divisibility and irreducibility results we also consider…

Number Theory · Mathematics 2021-09-27 Karl Dilcher , Maciej Ulas

In this note, we generalise two results on prime numbers in short intervals. The first result is Ingham's theorem which connects the zero-density estimates with short intervals where the prime number theorem holds, and the second result is…

Number Theory · Mathematics 2024-11-05 Valeriia Starichkova

We study cyclic binary strings with bounds on the lengths of the intervals of consecutive ones and zeros. This is motivated by scheduling problems where such binary strings can be used to represent the state (on/off) of a machine. In this…

Optimization and Control · Mathematics 2018-09-07 Thomas Kalinowski , Tomas Lidén , Hamish Waterer

We deal with countable alphabet locally compact random subshifts of finite type (the latter merely meaning that the symbol space is generated by an incidence matrix) under the absence of Big Images Property and under the absence of uniform…

Dynamical Systems · Mathematics 2015-09-02 Volker Mayer , Mariusz Urbanski

In this work, we revisit the problem of active sequential prediction-powered mean estimation, where at each round one must decide the query probability of the ground-truth label upon observing the covariates of a sample. Furthermore, if the…

Machine Learning · Statistics 2026-04-21 Maria-Eleni Sfyraki , Jun-Kun Wang

Let $b \geq 2$ be an integer and $S$ be a finite non-empty set of primes not containing divisors of $b$. For any non-dense set $A \subset [0,1)$ such that $A \cap \mathbb{Q}$ is invariant under $\times b$ operation, we prove the finiteness…

Number Theory · Mathematics 2022-04-18 Bing Li , Ruofan Li , Yufeng Wu

Post-selection inference has recently been proposed as a way of quantifying uncertainty about detected changepoints. The idea is to run a changepoint detection algorithm, and then re-use the same data to perform a test for a change near…

Methodology · Statistics 2026-05-11 Rachel Carrington , Paul Fearnhead

Recent work proposed the computation of so-called PI-explanations of Naive Bayes Classifiers (NBCs). PI-explanations are subset-minimal sets of feature-value pairs that are sufficient for the prediction, and have been computed with…

Machine Learning · Computer Science 2020-11-05 Joao Marques-Silva , Thomas Gerspacher , Martin C. Cooper , Alexey Ignatiev , Nina Narodytska