International Journal of Approximate Reasoning最新文献_第6页

Multi-label feature selection based on adaptive label enhancement and class-imbalance-aware fuzzy information entropy 基于自适应标签增强和类不平衡感知模糊信息熵的多标签特征选择

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-11-06 DOI: 10.1016/j.ijar.2024.109320

Qiong Liu , Mingjie Cai , Qingguo Li , Chaoqun Huang

{"title":"Multi-label feature selection based on adaptive label enhancement and class-imbalance-aware fuzzy information entropy","authors":"Qiong Liu , Mingjie Cai , Qingguo Li , Chaoqun Huang","doi":"10.1016/j.ijar.2024.109320","DOIUrl":"10.1016/j.ijar.2024.109320","url":null,"abstract":"<div><div>Multi-label feature selection can select representative features to reduce the dimension of data. Since existing multi-label feature selection methods usually suppose that the significance of all labels is consistent, the relationships between samples in the entire label space are generated straightforwardly such that the shape of label distribution and the property of class-imbalance are ignored. To address these issues, we propose a novel multi-label feature selection approach. Based on non-negative matrix factorization (NMF), the similarities between the logical label and label distribution are constrained, which ensures that the shape of label distribution does not deviate from the underlying actual shape to some extent. Further, the relationships between samples in label space and feature space are restricted by graph embedding. Finally, we leverage the properties of label distribution and class-imbalance to generate the relationships between samples in label space and propose a multi-label feature selection approach based on fuzzy information entropy. Eight state-of-the-art methods are compared with the proposed method to validate the effectiveness of our method.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"176 ","pages":"Article 109320"},"PeriodicalIF":3.2,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142654296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A three-way decision combining multi-granularity variable precision fuzzy rough set and TOPSIS method 多粒度可变精度模糊粗糙集与 TOPSIS 法相结合的三向决策

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-11-04 DOI: 10.1016/j.ijar.2024.109318

Chengzhao Jia, Lingqiang Li, Xinru Li

{"title":"A three-way decision combining multi-granularity variable precision fuzzy rough set and TOPSIS method","authors":"Chengzhao Jia, Lingqiang Li, Xinru Li","doi":"10.1016/j.ijar.2024.109318","DOIUrl":"10.1016/j.ijar.2024.109318","url":null,"abstract":"<div><div>This study proposed an innovative fuzzy rough set model to address multi-attribute decision-making problems. Initially, we introduced a novel model of multi-granularity variable precision fuzzy rough sets, which included three foundational models. This model was demonstrated to possess favorable algebraic and topological properties, and particularly noteworthy the comparable property. Subsequently, by integrating the novel model with the TOPSIS method, a novel three-way decision model was proposed. Within this framework, three fundamental models of multi-granularity variable precision fuzzy rough sets were applied in three methods to construct relative loss functions. This resulted in a three-way decision model with three distinct strategies. Finally, we implemented the proposed three-way decision model for risk detection in maternal women. Several experiments and comparisons were conducted to validate the effectiveness, stability, and reliability of our proposed approach. The experimental results indicated that the proposed method accurately classified and ranked maternal women. Overall, our approach offered multiple strategies and fault tolerance and was found to be effective for a large amount of data.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"176 ","pages":"Article 109318"},"PeriodicalIF":3.2,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Rough sets, modal logic and approximate reasoning 粗糙集、模态逻辑和近似推理

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-11-04 DOI: 10.1016/j.ijar.2024.109305

Mihir Kr. Chakraborty , Sandip Majumder , Samarjit Kar

引用次数: 0

Cauchy-Schwarz bounded trade-off weighting for causal inference with small sample sizes 用于小样本因果推断的考奇-施瓦茨有界权衡加权法

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-10-29 DOI: 10.1016/j.ijar.2024.109311

Qin Ma, Shikui Tu, Lei Xu

{"title":"Cauchy-Schwarz bounded trade-off weighting for causal inference with small sample sizes","authors":"Qin Ma, Shikui Tu, Lei Xu","doi":"10.1016/j.ijar.2024.109311","DOIUrl":"10.1016/j.ijar.2024.109311","url":null,"abstract":"<div><div>The difficulty of causal inference for small-sample-size data lies in the issue of inefficiency that the variance of the estimators may be large. Some existing weighting methods adopt the idea of bias-variance trade-off, but they require manual specification of the trade-off parameters. To overcome this drawback, in this article, we propose a Cauchy-Schwarz Bounded Trade-off Weighting (CBTW) method, in which the trade-off parameter is theoretically derived to guarantee a small Mean Square Error (MSE) in estimation. We theoretically prove that optimizing the objective function of CBTW, which is the Cauchy-Schwarz upper-bound of the MSE for causal effect estimators, contributes to minimizing the MSE. Moreover, since the upper-bound consists of the variance and the squared <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span>-norm of covariate differences, CBTW can not only estimate the causal effects efficiently, but also keep the covariates balanced. Experimental results on both simulation data and real-world data show that the CBTW outperforms most existing methods especially under small sample size scenarios.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"176 ","pages":"Article 109311"},"PeriodicalIF":3.2,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A 4-valued logic for double Stone algebras 双石代数的 4 值逻辑

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-10-24 DOI: 10.1016/j.ijar.2024.109309

Arun Kumar, Neha Gaur, Bisham Dewan

引用次数: 0

Convex expectations for countable-state uncertain processes with càdlàg sample paths 具有 càdlàg 样本路径的可数状态不确定过程的凸期望值

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-10-18 DOI: 10.1016/j.ijar.2024.109308

Alexander Erreygers

引用次数: 0

Approximate inference on optimized quantum Bayesian networks 优化量子贝叶斯网络的近似推理

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-10-17 DOI: 10.1016/j.ijar.2024.109307

Walid Fathallah , Nahla Ben Amor , Philippe Leray

{"title":"Approximate inference on optimized quantum Bayesian networks","authors":"Walid Fathallah , Nahla Ben Amor , Philippe Leray","doi":"10.1016/j.ijar.2024.109307","DOIUrl":"10.1016/j.ijar.2024.109307","url":null,"abstract":"<div><div>In recent years, there has been a significant upsurge in the interest surrounding Quantum machine learning, with researchers actively developing methods to leverage the power of quantum technology for solving highly complex problems across various domains. However, implementing gate-based quantum algorithms on noisy intermediate quantum devices (NISQ) presents notable challenges due to limited quantum resources and inherent noise. In this paper, we propose an innovative approach for representing Bayesian networks on quantum circuits, specifically designed to address these challenges and highlight the potential of combining optimized circuits with quantum hybrid algorithms for Bayesian network inference. Our aim is to minimize the required quantum resource needed to implement a Quantum Bayesian network (QBN) and implement quantum approximate inference algorithm on a quantum computer. Through simulations and experiments on IBM Quantum computers, we show that our circuit representation significantly reduces the resource requirements without decreasing the performance of the model. These findings underscore how our approach can better enable practical applications of QBN on currently available quantum hardware.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"175 ","pages":"Article 109307"},"PeriodicalIF":3.2,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A dissection of the monotonicity property of binary operations from a dominance point of view 从支配的角度剖析二元运算的单调性特性

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-10-11 DOI: 10.1016/j.ijar.2024.109304

Yuntian Wang , Lemnaouar Zedam , Bao Qing Hu , Bernard De Baets

引用次数: 0

Selected papers from the First International Joint Conference on Conceptual Knowledge Structures 第一届概念知识结构国际联合会议论文选

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-10-09 DOI: 10.1016/j.ijar.2024.109303

Inma P. Cabrera, Sébastien Ferré, Sergei Obiedkov

引用次数: 0

Iterative algorithms for solving one-sided partially observable stochastic shortest path games 求解单边部分可观测随机最短路径博弈的迭代算法

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-10-01 DOI: 10.1016/j.ijar.2024.109297

Petr Tomášek, Karel Horák, Branislav Bošanský

{"title":"Iterative algorithms for solving one-sided partially observable stochastic shortest path games","authors":"Petr Tomášek, Karel Horák, Branislav Bošanský","doi":"10.1016/j.ijar.2024.109297","DOIUrl":"10.1016/j.ijar.2024.109297","url":null,"abstract":"<div><div>Real-world scenarios often involve dynamic interactions among competing agents, where decisions are made considering actions taken by others. These situations can be modeled as partially observable stochastic games (<span>POSG</span>s), with zero-sum variants capturing strictly competitive interactions (e.g., security scenarios). While such models address a broad range of problems, they commonly focus on infinite-horizon scenarios with discounted-sum objectives. Using the discounted-sum objective, however, can lead to suboptimal solutions in cases where the length of the interaction does not directly affect the gained rewards of the players.</div><div>We thus focus on games with undiscounted objective and an indefinite horizon where every realization of the game is guaranteed to terminate after some unspecified number of turns. To manage the computational complexity of solving <span>POSG</span>s in general, we restrict to games with one-sided partial observability where only one player has imperfect information while their opponent is provided with full information about the current situation. We introduce two novel algorithms based on the heuristic search value iteration (<span>HSVI</span>) algorithm that iteratively solve sequences of easier-to-solve approximations of the game using fundamentally different approaches for constructing the sequences: (1) in <span>GoalHorizon</span>, the game approximations are based on a limited number of turns in which players can change their actions, (2) in <span>GoalDiscount</span>, the game approximations are constructed using an increasing discount factor. We provide theoretical qualitative guarantees for algorithms, and we also experimentally demonstrate that these algorithms are able to find near-optimal solutions on pursuit-evasion games and a game modeling privilege escalation problem from computer security.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"175 ","pages":"Article 109297"},"PeriodicalIF":3.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0