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Fuzzy implication functions are one of the most important operators used in the fuzzy logic framework. While their flexible definition allows for diverse families with distinct properties, this variety needs a deeper theoretical…

Artificial Intelligence · Computer Science 2025-09-23 Raquel Fernandez-Peralta , Juan Vicente Riera

Recent works by Bot-Fadili-Nguyen (arXiv:2510.22715) and by Jang-Ryu (arXiv:2510.23513) resolve long-standing iterate convergence questions for accelerated (proximal) gradient methods. In particular, Bot-Fadili-Nguyen prove weak convergence…

Optimization and Control · Mathematics 2025-11-11 Walaa M. Moursi , Andrew Naguib , Viktor Pavlovic , Stephen A. Vavasis

Fuzzy reasoning is a very productive research field that during the last years has provided a number of theoretical approaches and practical implementation prototypes. Nevertheless, the classical implementations, like Fril, are not adapted…

Programming Languages · Computer Science 2009-03-13 Victor Pablos Ceruelo , Susana Munoz-Hernandez , Hannes Strass

We consider minimization of functions that are compositions of convex or prox-regular functions (possibly extended-valued) with smooth vector functions. A wide variety of important optimization problems fall into this framework. We describe…

Optimization and Control · Mathematics 2015-04-24 A. S. Lewis , S. J. Wright

Affine point processes are a class of simple point processes with self- and mutually-exciting properties, and they have found useful applications in several areas. In this paper, we obtain large-time asymptotic expansions in large…

Probability · Mathematics 2019-07-26 Xuefeng Gao , Lingjiong Zhu

We propose Fuzzy Group Relative Policy Reward (FGRPR), a novel framework that integrates Group Relative Policy Optimization (GRPO) with a fuzzy reward function to enhance learning efficiency. Unlike the conventional binary 0/1 accuracy…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Zhiqiang Wang , Pengbin Feng , Yanbin Lin , Shuzhang Cai , Zongao Bian , Jinghua Yan , Xingquan Zhu

Robins et al. (2008) introduced a class of influence functions (IFs) which could be used to obtain doubly robust moment functions for the corresponding parameters. However, that class does not include the IF of parameters for which the…

Machine Learning · Statistics 2022-03-08 AmirEmad Ghassami , Andrew Ying , Ilya Shpitser , Eric Tchetgen Tchetgen

We suggest a new optimization technique for minimizing the sum $\sum_{i=1}^n f_i(x)$ of $n$ non-convex real functions that satisfy a property that we call piecewise log-Lipschitz. This is by forging links between techniques in computational…

Machine Learning · Computer Science 2019-09-10 Ibrahim Jubran , Dan Feldman

In this paper, we develop necessary and sufficient conditions for the validity of a martingale approximation for the partial sums of a stationary process in terms of the maximum of consecutive errors. Such an approximation is useful for…

Probability · Mathematics 2011-02-11 Mikhail Gordin , Magda Peligrad

In this paper, we introduce a method for approximating the solution to inference and optimization tasks in uncertain and deterministic reasoning. Such tasks are in general intractable for exact algorithms because of the large number of…

Artificial Intelligence · Computer Science 2012-12-12 David Ephraim Larkin

This work proposes the extended functional tensor train (EFTT) format for compressing and working with multivariate functions on tensor product domains. Our compression algorithm combines tensorized Chebyshev interpolation with a low-rank…

Numerical Analysis · Mathematics 2024-05-30 Christoph Strössner , Bonan Sun , Daniel Kressner

Given a set $F$ of $n$ positive functions over a ground set $X$, we consider the problem of computing $x^*$ that minimizes the expression $\sum_{f\in F}f(x)$, over $x\in X$. A typical application is \emph{shape fitting}, where we wish to…

Machine Learning · Computer Science 2016-05-31 Dan Feldman , Michael Langberg

This thesis investigates the extent to which the optimal value of a constraint satisfaction problem (CSP) can be approximated by some sentence of fixed point logic with counting (FPC). It is known that, assuming $\mathsf{P} \neq…

Logic in Computer Science · Computer Science 2020-08-10 Jamie Tucker-Foltz

Given sufficiently many components, it is often cited that finite mixture models can approximate any other probability density function (pdf) to an arbitrary degree of accuracy. Unfortunately, the nature of this approximation result is…

Statistics Theory · Mathematics 2020-08-24 T Tin Nguyen , Hien D Nguyen , Faicel Chamroukhi , Geoffrey J McLachlan

In the context of abstract coinduction in complete lattices, the notion of compatible function makes it possible to introduce enhancements of the coinduction proof principle. The largest compatible function, called the companion, subsumes…

Logic in Computer Science · Computer Science 2023-06-22 Damien Pous , Jurriaan Rot

This paper is concerned with the approximation of solutions to a class of second order non linear abstract differential equations. The finite-dimensional approximate solutions of the given system are built with the aid of the projection…

Numerical Analysis · Mathematics 2024-02-02 Shahin Ansari , Muslim Malik , Javid Ali

It is common in functional data analysis to look at a set of related functions: a set of learning curves, a set of brain signals, a set of spatial maps, etc. One way to express relatedness is through an additive model, whereby each…

Computation · Statistics 2014-02-21 Simon Barthelme

Let $A$ be a square complex matrix; $z_1$, ..., $z_{N}\in\mathbb C$ be arbitrary (possibly repetitive) points of interpolation; $f$ be an analytic function defined on a neighborhood of the convex hull of the union of the spectrum…

Numerical Analysis · Mathematics 2021-08-05 M. Ferus , V. G. Kurbatov , I. V. Kurbatova

We consider the class of counting problems,i.e. functions in $\#$P, which are self reducible, and have easy decision version, i.e. for every input it is easy to decide if the value of the function $f(x)$ is zero. For example,…

Computational Complexity · Computer Science 2016-11-08 Eleni Bakali

Interest in anti-unification, the dual problem of unification, is on the rise due to applications within the field of software analysis and related areas. For example, anti-unification-based techniques have found uses within clone detection…

Logic in Computer Science · Computer Science 2025-06-23 Mauricio Ayala-Rincon , David M. Cerna , Andres Felipe Gonzalez Barragan , Temur Kutsia
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