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We consider infinitely-wide multi-layer perceptrons (MLPs) which are limits of standard deep feed-forward neural networks. We assume that, for each layer, the weights of an MLP are initialized with i.i.d. samples from either a light-tailed…

Machine Learning · Statistics 2021-06-22 Paul Jung , Hoil Lee , Jiho Lee , Hongseok Yang

Diffusion Posterior Sampling (DPS) provides a principled Bayesian approach to inverse problems by sampling from $p(x_0 \mid y)$. While posterior sampling is valuable for capturing uncertainty and multi-modality, many classical and practical…

Graphics · Computer Science 2026-05-26 Shaorong Zhang , Rob Brekelmans , Greg Ver Steeg

We consider small perturbations of a dynamical system on the one-dimensional torus. We derive sharp estimates for the pre-factor of the stationary state, we examine the asymptotic behavior of the solutions of the Hamilton-Jacobi equation…

Probability · Mathematics 2017-10-19 C. Landim , I. Seo

We develop a Lyapunov-based analysis of Korpelevich's extragradient method and show that it achieves an $o(1/k)$ last-iterate convergence rate of the constructed Lyapunov function. This Lyapunov function simultaneously upper bounds several…

Optimization and Control · Mathematics 2026-01-21 Manu Upadhyaya , Puya Latafat , Pontus Giselsson

In this paper we introduce a ten-parameter family of L\'{e}vy processes for which we obtain Wiener-Hopf factors and distribution of the supremum process in semi-explicit form. This family allows an arbitrary behavior of small jumps and…

Probability · Mathematics 2010-11-09 Alexey Kuznetsov

In these lectures notes, we review our recent works addressing various problems of finding the nearest stable system to an unstable one. After the introduction, we provide some preliminary background, namely, defining Port-Hamiltonian…

Optimization and Control · Mathematics 2022-02-08 Nicolas Gillis , Punit Sharma

The nonlinear Fourier transform (NLFT) extends the classical Fourier transform by replacing addition with matrix multiplication. While the NLFT on $\mathrm{SU}(1,1)$ has been widely studied, its $\mathrm{SU}(2)$ variant has only recently…

Quantum Physics · Physics 2025-05-21 Hongkang Ni , Rahul Sarkar , Lexing Ying , Lin Lin

We consider an inverse shape problem for recovering an unknown simply supported obstacle in two dimensions from near--field point--source measurements for the biharmonic Helmholtz equation. The measured data consist of the scattered field…

Analysis of PDEs · Mathematics 2026-03-31 Isaac Harris , Andreas Kleefeld

The one-loop correction to heavy quark pair back-to-back production in unpolarized semi-inclusive deep inelastic scattering is given in this work in the framework of transverse momentum dependent(TMD) factorization. Both unpolarized and…

High Energy Physics - Phenomenology · Physics 2017-12-06 Guang-Peng Zhang

A robust algorithm for non-negative matrix factorization (NMF) is presented in this paper with the purpose of dealing with large-scale data, where the separability assumption is satisfied. In particular, we modify the Linear Programming…

Machine Learning · Statistics 2014-01-10 Jason Gejie Liu , Shuchin Aeron

The last couple of years has seen a remarkable number of new, explicit examples of the Wiener-Hopf factorization for Levy processes where previously there had been very few. We mention in particular the many cases of spectrally negative…

Probability · Mathematics 2011-04-12 Alexey Kuznetsov , Andreas E. Kyprianou , Juan Carlos Pardo

Using proof-theoretical techniques, we analyze a proof by H.-K. Xu regarding a result of strong convergence for the Halpern type proximal point algorithm. We obtain a rate of metastability (in the sense of T. Tao) and also a rate of…

Functional Analysis · Mathematics 2020-01-01 Pedro Pinto

There is an abundance of useful fluctuation identities for one-sided L\'evy processes observed up to an independent exponentially distributed time horizon. We show that all the fundamental formulas generalize to time horizons having matrix…

Probability · Mathematics 2021-01-21 Mogens Bladt , Jevgenijs Ivanovs

We characterize the value function and the optimal stopping time for a large class of optimal stopping problems where the underlying process to be stopped is a fairly general Markov process. The main result is inspired by recent findings…

Probability · Mathematics 2012-04-03 Sören Christensen , Paavo Salminen , Bao Quoc Ta

We propose a localized divide and conquer algorithm for inverse factorization $S^{-1} = ZZ^*$ of Hermitian positive definite matrices $S$ with localized structure, e.g. exponential decay with respect to some given distance function on the…

Numerical Analysis · Mathematics 2019-04-11 Emanuel H. Rubensson , Anton G. Artemov , Anastasia Kruchinina , Elias Rudberg

We (claim to) prove the extremely surprising fact that NP=RP. It is achieved by creating a Fully Polynomial-Time Randomized Approximation Scheme (FPRAS) for approximately counting the number of independent sets in bounded degree graphs,…

Computational Complexity · Computer Science 2020-08-06 András Faragó

Our companion paper \cite{Stojnicnflgscompyx23} introduced a very powerful \emph{fully lifted} (fl) statistical interpolating/comparison mechanism for bilinearly indexed random processes. Here, we present a particular realization of such fl…

Probability · Mathematics 2023-12-01 Mihailo Stojnic

We give a probabilistic proof of relative Fatou's theorem for $(-\Delta)^{\alpha/2}$-harmonic functions (equivalently for symmetric $\alpha$-stable processes) in bounded $\kappa$-fat open set where $\alpha \in (0,2)$. That is, if $u$ is…

Probability · Mathematics 2007-05-23 Panki Kim

We study a general factor analysis framework where the $n$-by-$p$ data matrix is assumed to follow a general exponential family distribution entry-wise. While this model framework has been proposed before, we here further relax its…

Methodology · Statistics 2025-12-02 Liang Wang , Luis Carvalho

We present the submatrix method, a highly parallelizable method for the approximate calculation of inverse p-th roots of large sparse symmetric matrices which are required in different scientific applications. We follow the idea of…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-03-06 Michael Lass , Stephan Mohr , Hendrik Wiebeler , Thomas D. Kühne , Christian Plessl