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In this paper, we analyze the generalization performance of the Iterative Hard Thresholding (IHT) algorithm widely used for sparse recovery problems. The parameter estimation and sparsity recovery consistency of IHT has long been known in…

Machine Learning · Statistics 2022-03-18 Xiao-Tong Yuan , Ping Li

This paper is devoted to the study of the expected-integral multifunctions given in the form \begin{equation*} \operatorname{E}_\Phi(x):=\int_T\Phi_t(x)d\mu, \end{equation*} where $\Phi\colon T\times\mathbb{R}^n \rightrightarrows…

Optimization and Control · Mathematics 2021-06-21 Boris S. Mordukhovich , Pedro Pérez-Aros

We study the problem of mismatched binary hypothesis testing between i.i.d. distributions. We analyze the tradeoff between the pairwise error probability exponents when the actual distributions generating the observation are different from…

Information Theory · Computer Science 2022-04-28 Parham Boroumand , Albert Guillén i Fàbregas

Let us assume that $f$ is a continuous function defined on the unit ball of $\mathbb R^d$, of the form $f(x) = g (A x)$, where $A$ is a $k \times d$ matrix and $g$ is a function of $k$ variables for $k \ll d$. We are given a budget $m \in…

Numerical Analysis · Mathematics 2012-01-18 Massimo Fornasier , Karin Schnass , Jan Vybiral

We consider the problem where an active Decision-Maker (DM) is tasked to identify the true hypothesis using as few samples as possible while maintaining accuracy. The DM collects samples according to its determined actions and knows the…

Information Theory · Computer Science 2025-10-01 George Vershinin , Asaf Cohen , Omer Gurewitz

We consider a stationary linear AR($p$) model with observations subject to gross errors (outliers). The autoregression parameters as well as the distribution function (d.f.) $G$ of innovations are unknown. The distribution of outliers $\Pi$…

Statistics Theory · Mathematics 2020-04-15 Michael Boldin

In this paper, we study the estimation of the derivative of a regression function in a standard univariate regression model. The estimators are defined either by derivating nonparametric least-squares estimators of the regression function…

Statistics Theory · Mathematics 2023-11-13 Fabienne Comte , Nicolas Marie

Let $\lambda$ denote the Liouville function. We show that as $X \rightarrow \infty$, $$ \int_{X}^{2X} \sup_{\alpha} \left | \sum_{x < n \leq x + H} \lambda(n) e(-\alpha n) \right | dx = o ( X H) $$ for all $H \geq X^{\theta}$ with $\theta >…

Number Theory · Mathematics 2018-12-05 Kaisa Matomäki , Maksym Radziwiłł , Terence Tao

Consider a Markov chain $(X_i)_{i\ge0}$ with invariant measure $\mu$ that admits the representation $X_{i+1}=\Phi(X_i,U_i)$, where $(U_i)_{i\ge0}$ are i.i.d. random variables and $\Phi$ is a measurable map. We introduce a tangent-decoupled…

Probability · Mathematics 2025-12-23 Nawaf Bou-Rabee , Victor H. de la Peña

This paper studies inference in randomized controlled trials with covariate-adaptive randomization when there are multiple treatments. More specifically, we study inference about the average effect of one or more treatments relative to…

Econometrics · Economics 2019-01-21 Federico A. Bugni , Ivan A. Canay , Azeem M. Shaikh

In this paper, we study the functional convergence in law of the fluctuations of the derivative martingale of branching random walk on the real line. Our main result strengthens the results of Buraczewski et. al. [Ann. Probab., 2021] and is…

Probability · Mathematics 2023-11-29 Haojie Hou , Yan-Xia Ren , Renming Song

Consider a Moran-type iterated function system (IFS) \( \{\phi_{k,d}\}_{d\in D_{2p_k}, k\geq 1} \), where each contraction map is defined as \[ \phi_{k,d}(x) = (-1)^d b_k^{-1}(x + d), \] with integer sequences \( \{b_k\}_{k=1}^\infty \) and…

Functional Analysis · Mathematics 2025-04-04 Jun Jason Luo , Lin Mao , Jing-Cheng Liu

Although there is an extensive body of work characterizing the sample complexity of discounted-return offline RL with function approximations, prior work on the average-reward setting has received significantly less attention, and existing…

Machine Learning · Computer Science 2025-10-21 Jongmin Lee , Ernest K. Ryu

We perform a Bayesian study of a generalization of the basic $\alpha$-attractor T model given by the potential $V(\phi)=V_0\left[1-\text{sech}^{p}\left(\phi/\sqrt{6\alpha}M_{pl}\right)\right]$ where $\phi$ is the inflaton field and the…

Cosmology and Nongalactic Astrophysics · Physics 2023-07-12 Francisco X. Linares Cedeño , Gabriel German , Juan Carlos Hidalgo , Ariadna Montiel

We extend classical basis constructions from Fourier analysis to attractors for affine iterated function systems (IFSs). This is of interest since these attractors have fractal features, e.g., measures with fractal scaling dimension.…

Classical Analysis and ODEs · Mathematics 2008-02-13 Dorin Ervin Dutkay , Palle E. T. Jorgensen

We show that if $\lbrace \varphi_i\rbrace_{i\in \Gamma}$ and $\lbrace \psi_j\rbrace_{j\in\Lambda}$ are self-affine iterated function systems on the plane that satisfy strong separation, domination and irreducibility, then for any associated…

Classical Analysis and ODEs · Mathematics 2024-05-30 Aleksi Pyörälä

Statistically self-similar measures on $[0,1]$ are limit of multiplicative cascades of random weights distributed on the $b$-adic subintervals of $[0,1]$. These weights are i.i.d, positive, and of expectation $1/b$. We extend these cascades…

Probability · Mathematics 2009-02-18 Julien Barral , Benoit Mandelbrot

We apply a suitable modification of the functional delta method to statistical functionals that arise from law-invariant coherent risk measures. To this end we establish differentiability of the statistical functional in a relaxed Hadamard…

Statistics Theory · Mathematics 2015-02-18 Volker Krätschmer , Alexander Schied , Henryk Zähle

In many textbooks on Generalized Functions and Distributions, we can find an example of infinitely differentiable function of bounded support from space D, called a bump function. This example is incorrect since this function is not…

Mathematical Physics · Physics 2012-07-27 A. Tsionskiy , M. Tsionskiy

Measuring functional connectivity from fMRI is important in understanding processing in cortical networks. However, because brain's connection pattern is complex, currently used methods are prone to produce false connections. We introduce…

Neurons and Cognition · Quantitative Biology 2020-06-23 Tiger w. Lin , Giri P. Krishnan , Maxim Bazhenov , Terrence J. Sejnowski