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Simultaneous inference allows for the exploration of data while deciding on criteria for proclaiming discoveries. It was recently proved that all admissible post-hoc inference methods for true discoveries must employ closed testing. In this…

Statistics Theory · Mathematics 2022-03-24 Jinjin Tian , Xu Chen , Eugene Katsevich , Jelle Goeman , Aaditya Ramdas

Probabilistic programs encode stochastic models as ordinary-looking programs with primitives for sampling numbers from predefined distributions and conditioning. Their applications include, among many others, machine learning and modeling…

Formal Languages and Automata Theory · Computer Science 2025-12-16 Dominik Geißler , Tobias Winkler

Simulating quantum circuits using classical computers lets us analyse the inner workings of quantum algorithms. The most complete type of simulation, strong simulation, is believed to be generally inefficient. Nevertheless, several…

Quantum Physics · Physics 2013-02-25 T. H. Johnson , J. D. Biamonte , S. R. Clark , D. Jaksch

We simulate the distribution of very rare, large excursions in the primordial density field produced in models of inflation in the very early universe which include a strong enhancement of the power spectrum. The stochastic $\delta…

Cosmology and Nongalactic Astrophysics · Physics 2025-04-25 Joseph H. P. Jackson , Hooshyar Assadullahi , Andrew D. Gow , Kazuya Koyama , Vincent Vennin , David Wands

We place ourselves in a functional regression setting and propose a novel methodology for regressing a real output on vector-valued functional covariates. This methodology is based on the notion of signature, which is a representation of a…

Methodology · Statistics 2022-06-17 Adeline Fermanian

Let $p$ be an odd prime and let $f(x)=\sum_{i=1}^ka_ix^{p^{\alpha_i}+1}\in\Bbb F_{p^n}[x]$, where $0\le \alpha_1<...<\alpha_k$. We consider the exponential sum $S(f,n)=\sum_{x\in\Bbb F_{p^n}}e_n(f(x))$, where $e_n(y)=e^{2\pi…

Number Theory · Mathematics 2007-08-28 Sandra Draper , Xiang-dong Hou

The takeoff point for this paper is the voluminous body of literature addressing recursive betting games with expected logarithmic growth of wealth being the performance criterion. Whereas almost all existing papers involve use of linear…

Optimization and Control · Mathematics 2024-01-17 Anton V. Proskurnikov , B. Ross Barmish

Diffusion models are a remarkably effective way of learning and sampling from a distribution $p(x)$. In posterior sampling, one is also given a measurement model $p(y \mid x)$ and a measurement $y$, and would like to sample from $p(x \mid…

Machine Learning · Computer Science 2025-11-11 Shivam Gupta , Ajil Jalal , Aditya Parulekar , Eric Price , Zhiyang Xun

We consider a random self-affine carpet $F$ based on an $n\times m$ subdivision of rectangles and a probability $0<p<1$. Starting by dividing $[0,1]^2$ into an $n\times m$ grid of rectangles and selecting these independently with…

Metric Geometry · Mathematics 2024-09-11 Kenneth Falconer , Tianyi Feng

There has been a great deal of recent interest in methods for performing lifted inference; however, most of this work assumes that the first-order model is given as input to the system. Here, we describe lifted inference algorithms that…

Artificial Intelligence · Computer Science 2012-05-14 Prithviraj Sen , Amol Deshpande , Lise Getoor

Numerical simulation codes are very common tools to study complex phenomena, but they are often time-consuming and considered as black boxes. For some statistical studies (e.g. asset management, sensitivity analysis) or optimization…

Statistics Theory · Mathematics 2017-08-14 Vincent Moutoussamy , Simon Nanty , Benoît Pauwels

We study a sequential coin-flipping game in which a player starts with~$n$ coins, each landing heads independently with probability~$p$. In each round the player flips all remaining coins and must set aside at least one coin showing heads;…

Probability · Mathematics 2026-04-28 Peter Pfaffelhuber

Across many domains of science, stochastic models are an essential tool to understand the mechanisms underlying empirically observed data. Models can be of different levels of detail and accuracy, with models of high-fidelity (i.e., high…

Many conventional statistical procedures are extremely sensitive to seemingly minor deviations from modeling assumptions. This problem is exacerbated in modern high-dimensional settings, where the problem dimension can grow with and…

Machine Learning · Statistics 2017-02-27 Simon S. Du , Sivaraman Balakrishnan , Aarti Singh

The study of semifeasible algorithms was initiated by Selman's work a quarter of century ago [Sel79,Sel81,Sel82]. Informally put, this research stream studies the power of those sets L for which there is a deterministic (or in some cases,…

Computational Complexity · Computer Science 2007-05-23 Piotr Faliszewski , Lane A. Hemaspaandra

This article presents a novel, general, and effective simulation-inspired approach, called {\it repro samples method}, to conduct statistical inference. The approach studies the performance of artificial samples, referred to as {\it repro…

Methodology · Statistics 2022-06-15 Min-ge Xie , Peng Wang

Let $r,\,f$ be multiplicative functions with $r\geqslant 0$, $f$ is complex valued, $|f|\leqslant r$, and $r$ satisfies some standard growth hypotheses. Let $x$ be large, and assume that, for some real number $\tau$, the quantities…

Number Theory · Mathematics 2025-12-19 Gérald Tenenbaum

In the game of Matching Pennies, Alice and Bob each hold a penny, and at every tick of the clock they simultaneously display the head or the tail sides of their coins. If they both display the same side, then Alice wins Bob's penny; if they…

Computer Science and Game Theory · Computer Science 2018-02-05 Dusko Pavlovic , Peter-Michael Seidel , Muzamil Yahia

We propose a general formalism of iterated random functions with semigroup property, under which exact and approximate Bayesian posterior updates can be viewed as specific instances. A convergence theory for iterated random functions is…

Machine Learning · Statistics 2013-11-05 Arash A. Amini , XuanLong Nguyen

Given a sequence of independent Bernoulli variables with unknown parameter $p$, and a function $f$ expressed as a power series with non-negative coefficients that sum to at most $1$, an algorithm is presented that produces a Bernoulli…

Statistics Theory · Mathematics 2024-11-26 Luis Mendo