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Adjoint operators have been found to be effective in the exploration of CNN's inner workings [1]. However, the previous no-bias assumption restricted its generalization. We overcome the restriction via embedding input images into an…

Machine Learning · Computer Science 2023-11-10 Qing Wan , Siu Wun Cheung , Yoonsuck Choe

Employing hamiltonians defined by two-body embedded Gaussian orthogonal ensemble of random matrices(EGOE(2)) plus a mean-field producing one-body part, strength functions (for states defined by the one-body part) are constructed for various…

Nuclear Theory · Physics 2007-05-23 V. K. B. Kota , R. Sahu

We describe a new MCMC method optimized for the sampling of probability measures on Hilbert space which have a density with respect to a Gaussian; such measures arise in the Bayesian approach to inverse problems, and in conditioned…

Probability · Mathematics 2014-04-04 Michela Ottobre , Natesh S. Pillai , Frank J. Pinski , Andrew M. Stuart

Monte Carlo (MC) and Quasi-Monte Carlo (QMC) methods are classical approaches for the numerical integration of functions $f$ over $[0,1]^d$. While QMC methods can achieve faster convergence rates than MC in moderate dimensions, their…

Numerical Analysis · Mathematics 2025-08-27 Jiaheng Chen , Haotian Jiang , Nathan Kirk

This paper focuses on estimating the Taylor coefficients for Hilbert spaces of holomorphic functions on the disk using intrinsic features of univalent functions and of Teichmuller spaces. Estimating these coefficients has a long history but…

Complex Variables · Mathematics 2026-05-20 Samuel L Krushkal

Two algorithms for solving misalignment issues in penalized PET/CT reconstruction using anatomical priors are proposed. Both approaches are based on a recently published joint motion estimation and image reconstruction method. The first…

Let $G$ be a finite abelian group acting faithfully on a finite set $X$. As a natural generalization of the perfect nonlinearity of Boolean functions, the $G$-bentness and $G$-perfect nonlinearity of functions on $X$ are studied by Poinsot…

Discrete Mathematics · Computer Science 2014-06-18 Yun Fan , Bangteng Xu

Model merging aims to combine multiple fine-tuned models into a single set of weights that performs well across all source tasks. While prior work has shown that merging can approximate the performance of individual fine-tuned models for…

Machine Learning · Computer Science 2025-10-17 Mohammadsajad Alipour , Mohammad Mohammadi Amiri

In this document I develop a weight function theory of positive order basis function interpolants and smoothers. **In Chapter 1 the basis functions and data spaces are defined directly using weight functions. The data spaces are used to…

Numerical Analysis · Mathematics 2014-03-28 Phillip Y. Williams

A challenging problem in many modern machine learning tasks is to process weight-space features, i.e., to transform or extract information from the weights and gradients of a neural network. Recent works have developed promising…

Machine Learning · Computer Science 2024-02-09 Allan Zhou , Chelsea Finn , James Harrison

In Pasalic et al., IEEE Trans. Inform. Theory 69 (2023), 2702--2712, and in Anbar, Meidl, Cryptogr. Commun. 10 (2018), 235--249, two different vectorial negabent and vectorial bent-negabent concepts are introduced, which leads to seemingly…

Combinatorics · Mathematics 2024-02-09 Nurdagül Anbar , Sadmir Kudin , Wilfried Meidl , Enes Pasalic , Alexandr Polujan

This research aimed to introduce the concept of harmonically m-concave set-valued functions, which is obtained from the combination of two definitions: harmonically m-concave functions and set-valued functions. In this work some properties…

Functional Analysis · Mathematics 2024-03-13 Gabriel Santana , Maira Valera-López , Nelson Merentes

Weight-space merging aims to combine multiple fine-tuned LLMs into a single model without retraining, yet most existing approaches remain fundamentally parameter-space heuristics. This creates three practical limitations. First, linear…

Machine Learning · Computer Science 2026-03-06 Jiayu Wang , Zuojun Ye , Wenpeng Yin

This paper introduces Targeted Function Balancing (TFB), a covariate balancing weights framework for estimating the average treatment effect of a binary intervention. TFB first regresses an outcome on covariates, and then selects weights…

Methodology · Statistics 2025-04-10 Leonard Wainstein , He Bai

We consider mixed type multiple orthogonal polynomials associated with a system of weight functions consisting of two vectors. One vector is defined in terms of scaled modified Bessel function of the first kind $I_\mu$ and $I_{\mu+1}$, the…

Classical Analysis and ODEs · Mathematics 2016-09-28 Lun Zhang

Potential functions can be used as generating potentials of relevant geometric structures for a Riemannian manifold such as the Riemannian metric and affine connections. We study wether this procedure can also be applied to tensors of rank…

Differential Geometry · Mathematics 2019-02-04 Florio M. Ciaglia , Giuseppe Marmo , Juan Manuel Pérez-Pardo

Given two martingales on the filtration generated by two dimensional Brownian motion, we want to estimate the $L^p$ norm of the subordinated one if we have some extra orthogonality property available. We construct several new Bellman…

Probability · Mathematics 2010-12-07 Prabhu Janakiraman , Vasily Vasyunin , Alexander Volberg

In a recent preprint, Lai showed that the quotient of generating functions of weighted lozenge tilings of two "half hexagons with lateral dents", which differ only in width, factors nicely, and the same is true for the quotient of…

Combinatorics · Mathematics 2020-12-15 Markus Fulmek

Recently there has been progress on the calculation of three-point functions with two "heavy" operators via semiclassical methods. We extend this analysis to the case of the Lunin-Maldacena background, and examine the suggested procedure…

High Energy Physics - Theory · Physics 2013-05-29 D. Arnaudov , R. C. Rashkov

In this paper, one new classes of convex functions which is called MT-convex functions are given. We also establish some Hadamard-type inequalities.

Classical Analysis and ODEs · Mathematics 2012-05-25 Mevlut Tunc , Huseyin Yildirim
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