253 citations · 1.2k across the 46 of their papers we have counts for
13 papers · 1 filter
A Boundary-Aware Non-parametric Granular-Ball Classifier Based on Minimum Description Length
Zeqiang Xian, Caihui Liu, Yong Zhang +3
Existing granular-ball classification methods are often driven by handcrafted quality measures, neighborhood rules, or heuristic splitting and stopping criteria, which may reduce t…
MDL-GBG: A Non-parametric and Interpretable Granular-Ball Generation Method for Clustering
Zeqiang Xian, Caihui Liu, Yong Zhang +3
Existing granular-ball generation methods are still mainly driven by handcrafted quality measures and heuristic splitting or stopping criteria, which may weaken the transparency of…
Ensemble Reinforcement Learning: A Survey
Yanjie Song, P. N. Suganthan, Witold Pedrycz +4
Reinforcement Learning (RL) has emerged as a highly effective technique for addressing various scientific and applied problems. Despite its success, certain complex tasks remain ch…
Accelerated Fuzzy C-Means Clustering Based on New Affinity Filtering and Membership Scaling
Dong Li, Shuisheng Zhou, Witold Pedrycz
Fuzzy C-Means (FCM) is a widely used clustering method. However, FCM and its many accelerated variants have low efficiency in the mid-to-late stage of the clustering process. In th…
Heterogeneous Graph Neural Networks using Self-supervised Reciprocally Contrastive Learning
Cuiying Huo, Dongxiao He, Yawen Li +5
Heterogeneous graph neural network (HGNN) is a very popular technique for the modeling and analysis of heterogeneous graphs. Most existing HGNN-based approaches are supervised or s…
An Overview and Experimental Study of Learning-based Optimization Algorithms for Vehicle Routing Problem
Bingjie Li, Guohua Wu, Yongming He +2
Vehicle routing problem (VRP) is a typical discrete combinatorial optimization problem, and many models and algorithms have been proposed to solve the VRP and its variants. Althoug…
Exponentially Weighted l_2 Regularization Strategy in Constructing Reinforced Second-order Fuzzy Rule-based Model
Congcong Zhang, Sung-Kwun Oh, Witold Pedrycz +2
In the conventional Takagi-Sugeno-Kang (TSK)-type fuzzy models, constant or linear functions are usually utilized as the consequent parts of the fuzzy rules, but they cannot effect…
Granular Computing: An Augmented Scheme of Degranulation Through a Modified Partition Matrix
Kaijie Xu, Witold Pedrycz, Zhiwu Li +1
As an important technology in artificial intelligence Granular Computing (GrC) has emerged as a new multi-disciplinary paradigm and received much attention in recent years. Informa…
The Learning of Fuzzy Cognitive Maps With Noisy Data: A Rapid and Robust Learning Method With Maximum Entropy
Guoliang Feng, Wei Lu, Witold Pedrycz +2
Numerous learning methods for fuzzy cognitive maps (FCMs), such as the Hebbian-based and the population-based learning methods, have been developed for modeling and simulating dyna…
Online Tool Condition Monitoring Based on Parsimonious Ensemble+
Mahardhika Pratama, Eric Dimla, Edwin Lughofer +2
Accurate diagnosis of tool wear in metal turning process remains an open challenge for both scientists and industrial practitioners because of inhomogeneities in workpiece material…
Evolving Ensemble Fuzzy Classifier
Mahardhika Pratama, Witold Pedrycz, Edwin Lughofer
The concept of ensemble learning offers a promising avenue in learning from data streams under complex environments because it addresses the bias and variance dilemma better than i…
Aggregation of Classifiers: A Justifiable Information Granularity Approach
Tien Thanh Nguyen, Xuan Cuong Pham, Alan Wee-Chung Liew +1
In this study, we introduce a new approach to combine multi-classifiers in an ensemble system. Instead of using numeric membership values encountered in fixed combining rules, we c…
Global and Local Structure Preserving Sparse Subspace Learning: An Iterative Approach to Unsupervised Feature Selection
Nan Zhou, Yangyang Xu, Hong Cheng +2
As we aim at alleviating the curse of high-dimensionality, subspace learning is becoming more popular. Existing approaches use either information about global or local structure of…