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Related papers: Soft Approximations and uni-int Decision Making

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PointNet, which is the widely used point-wise embedding method and known as a universal approximator for continuous set functions, can process one million points per second. Nevertheless, real-time inference for the recent development of…

Computer Vision and Pattern Recognition · Computer Science 2020-10-09 Teppei Suzuki , Keisuke Ozawa , Yusuke Sekikawa

In practical situations, calculating approximations of concepts is the central step for knowledge reduction of dynamic covering decision information system, which has received growing interests of researchers in recent years. In this paper,…

Information Theory · Computer Science 2015-12-10 Guangming Lang

Decision-making is a process of choosing among alternative courses of action for solving complicated problems where multi-criteria objectives are involved. The past few years have witnessed a growing recognition of Soft Computing…

Artificial Intelligence · Computer Science 2016-11-17 Cong Tran , Ajith Abraham , Lakhmi Jain

First of all, we focused soft {\beta}-open sets and soft {\beta}-closed sets over the soft topological space and investigated some properties of them. Secondly, we defined the concepts soft {\beta}-continuity, soft {\beta}-irresolute and…

General Topology · Mathematics 2013-12-30 Yunus Yumak , Aynur Keskin Kaymakcı

Representational similarity metrics typically force all units to be matched, making them susceptible to noise and outliers common in neural representations. We extend the soft-matching distance to a partial optimal transport setting that…

Machine Learning · Computer Science 2026-02-24 Chaitanya Kapoor , Alex H. Williams , Meenakshi Khosla

Clustering based on belief functions has been gaining increasing attention in the machine learning community due to its ability to effectively represent uncertainty and/or imprecision. However, none of the existing algorithms can be applied…

Machine Learning · Computer Science 2025-07-21 Armel Soubeiga , Thomas Guyet , Violaine Antoine

Soft robotics are increasingly favoured in specific applications such as healthcare, due to their adaptability, which stems from the non-linear properties of their building materials. However, these properties also pose significant…

Emerging Technologies · Computer Science 2025-10-29 Hugo Alcaraz-Herrera , Michail-Antisthenis Tsompanas , Igor Balaz , Andrew Adamatzky

From last decade, when Molodtsov introduced the theory of soft set as a new approach to deal with uncertainties, until now this theory was considered sharply by a fair number of researchers. Combination of fuzzy set theory and soft set…

Functional Analysis · Mathematics 2013-09-20 Azadeh Zahedi Khameneh , Adem Kilicman , Abdul Razak Salleh

Consider the following variant of the set cover problem. We are given a universe $U=\{1,...,n\}$ and a collection of subsets $\mathcal{C} = \{S_1,...,S_m\}$ where $S_i \subseteq U$. For every element $u \in U$ we need to find a set $\phi(u)…

Computational Complexity · Computer Science 2017-07-07 Marek Adamczyk , Fabrizio Grandoni , Stefano Leonardi , MIchal Wlodarczyk

The present paper comes across the main steps that laid from Zadeh's fuzziness ana Atanassov's intuitionistic fuzzy sets to Smarandache's indeterminacy and to Molodstov's soft sets. Two hybrid methods for assessment and decision making…

Artificial Intelligence · Computer Science 2022-11-29 Michael Gr. Voskoglou

We propose a data-driven technique to automatically learn contextual uncertainty sets in robust optimization, resulting in excellent worst-case and average-case performance while also guaranteeing constraint satisfaction. Our method…

Optimization and Control · Mathematics 2025-06-25 Irina Wang , Bart Van Parys , Bartolomeo Stellato

This article is devoted to one particular case of using universal accelerated proximal envelopes to obtain computationally efficient accelerated versions of methods used to solve various optimization problem setups. In this paper, we…

Optimization and Control · Mathematics 2021-01-14 Dmitry Pasechnyuk , Anton Anikin , Vladislav Matyukhin

Study of soft sets was first proposed by Molodtsov in 1999 to deal with uncertainty in a non-parametric manner. The researchers did not pay attention to soft set theory at that time but now the soft set theory has been developed in many…

Artificial Intelligence · Computer Science 2014-08-26 Florentin Smarandache , Mumtaz Ali , Muhammad Shabir

This study presents an enhanced proprioceptive method for accurate shape estimation of soft robots using only off-the-shelf sensors, ensuring cost-effectiveness and easy applicability. By integrating inertial measurement units (IMUs) with…

Robotics · Computer Science 2025-11-04 Dong Heon Han , Mayank Mehta , Runze Zuo , Zachary Wanger , Daniel Bruder

This paper presents a comprehensive analysis of a broad range of variations of the stochastic proximal point method (SPPM). Proximal point methods have attracted considerable interest owing to their numerical stability and robustness…

Optimization and Control · Mathematics 2024-05-28 Peter Richtárik , Abdurakhmon Sadiev , Yury Demidovich

Fixpoints are ubiquitous in computer science and when dealing with quantitative semantics and verification one often considers least fixpoints of (higher-dimensional) functions over the non-negative reals. We show how to approximate the…

Logic in Computer Science · Computer Science 2025-06-16 Paolo Baldan , Sebastian Gurke , Barbara König , Tommaso Padoan , Florian Wittbold

In this article, we define some types of distances between two intuitionistic fuzzy soft (IFS) sets and proposed similarity measures of two IFS-sets. We then construct a decision method which is applied to a medical diagnosis problem that…

Logic · Mathematics 2013-12-17 Naim Çağman , İrfan Deli

Soft materials play an integral part in many aspects of modern life including autonomy, sustainability, and human health, and their accurate modeling is critical to understand their unique properties and functions. Today's finite element…

Computational Engineering, Finance, and Science · Computer Science 2024-09-24 Mathias Peirlinck , Juan A. Hurtado , Manuel K. Rausch , Adrian Buganza Tepole , Ellen Kuhl

This paper studies and bounds the effects of approximating loss functions and credal sets on choice functions, under very weak assumptions. In particular, the credal set is assumed to be neither convex nor closed. The main result is that…

Computation · Statistics 2012-03-06 Matthias C. M. Troffaes

We define a new class of set functions that in addition to being monotone and subadditive, also admit a very limited form of submodularity defined over a permutation of the ground set. We refer to this permutation as a submodular order.…

Optimization and Control · Mathematics 2024-03-01 Rajan Udwani