Witold Pedrycz
9 أوراق في مجموعة PaperMetrix
أوراق هذا المؤلف
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Entropic One-Class Classifiers
2015 · IEEE Transactions on Neural Networks and Learning Systems
The one-class classification problem is a well-known research endeavor in pattern recognition. The problem is also known under different names, such as outlier and novelty/anomaly detection. The core of the problem consists in modeling and …
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Genetic-Programming-Based Architecture of Fuzzy Modeling: Towards Coping With High-Dimensional Data
2020 · IEEE Transactions on Fuzzy Systems
This article is concerned with the development of fuzzy models realized with the aid of genetic programming (GP). The proposed architecture employs GP to form fuzzy logic expressions involving logic operators and information granules (fuzzy …
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Amer: A New Attribute-Missing Network Embedding Approach
2022 · IEEE Transactions on Cybernetics
Network embedding which aims to learn a low dimensional representation of nodes is a powerful technique for network analysis. While network embedding for networks with complete attributes has been widely investigated, in many real-world applications …
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An Approach to Semantic-Aware Heterogeneous Network Embedding for Recommender Systems
2023 · IEEE Transactions on Cybernetics
Recent studies on heterogeneous information network (HIN) embedding-based recommendations have encountered challenges. These challenges are related to the data heterogeneity of the associated unstructured attribute or content (e.g., text-based summary/description) of users and items in …
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Time Series Anomaly Detection via Rectangular Information Granulation for Sintering Process
2024 · IEEE Transactions on Fuzzy Systems
Time series anomaly in the sintering process is a direct manifestation of equipment failure and abnormal operating mode, and effective detection of time series anomaly is important to improve the stability of the sintering process. …
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Bridging Visualization and Optimization: Multimodal Large Language Models on Graph-Structured Combinatorial Optimization
2025 · arXiv (Cornell University)
Graph-structured combinatorial challenges are inherently difficult due to their nonlinear and intricate nature, often rendering traditional computational methods ineffective or expensive. However, these challenges can be more naturally tackled by humans through visual representations that …
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Multiple Self-Adaptive Correlation-Based Multiview Multilabel Learning
2025 · IEEE Transactions on Cybernetics
In order to process multiview multilabel, multilabel, and multiview data, current learning algorithms are designed on the basis of data characteristics, correlations, etc. While these algorithms cannot express correlations among different features, instances, labels in …
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An Adaptive Federated Fuzzy C-Means Clustering With Nonindependently and Identically Distributed Data
2025 · IEEE Transactions on Systems Man and Cybernetics Systems
Federated Fuzzy C-Means (FCM) has received considerable attention due to the increasing need for privacy-conscious data analysis across diverse domains and sources in many real-world applications. Recent developments in federated FCM, however, are still in …
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Robust Semi-Supervised Feature Selection With Multi-Granularity Zentropy Modeling
2025 · IEEE Transactions on Pattern Analysis and Machine Intelligence
High-dimensional and weakly supervised (HiDWS) data present significant challenges for traditional machine learning and pattern recognition. Although semi-supervised feature selection has shown effectiveness in improving the quality of HiDWS data, existing methods remain sensitive and …