Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Akhtar, Mushir"'
Alzheimer's disease (AD) is a leading neurodegenerative condition and the primary cause of dementia, characterized by progressive cognitive decline and memory loss. Its progression, marked by shrinkage in the cerebral cortex, is irreversible. Numerou
Externí odkaz:
http://arxiv.org/abs/2410.14207
Publikováno v:
27th International Conference on Pattern Recognition (ICPR), 2024
In this paper, we propose enhanced feature based granular ball twin support vector machine (EF-GBTSVM). EF-GBTSVM employs the coarse granularity of granular balls (GBs) as input rather than individual data samples. The GBs are mapped to the feature s
Externí odkaz:
http://arxiv.org/abs/2410.05786
Publikováno v:
31st International Conference on Neural Information Processing (ICONIP), 2024
Random vector functional link (RVFL), a variant of single-layer feedforward neural network (SLFN), has garnered significant attention due to its lower computational cost and robustness to overfitting. Despite its advantages, the RVFL network's relian
Externí odkaz:
http://arxiv.org/abs/2410.00510
Publikováno v:
27th International Conference on Pattern Recognition (ICPR), 2024
Twin support vector machine (TSVM), a variant of support vector machine (SVM), has garnered significant attention due to its $3/4$ times lower computational complexity compared to SVM. However, due to the utilization of the hinge loss function, TSVM
Externí odkaz:
http://arxiv.org/abs/2408.16336
Multiview learning (MvL) is an advancing domain in machine learning, leveraging multiple data perspectives to enhance model performance through view-consistency and view-discrepancy. Despite numerous successful multiview-based SVM models, existing fr
Externí odkaz:
http://arxiv.org/abs/2408.06819
Publikováno v:
Pattern Recognition, Elsevier (2024)
Loss function plays a vital role in supervised learning frameworks. The selection of the appropriate loss function holds the potential to have a substantial impact on the proficiency attained by the acquired model. The training of supervised learning
Externí odkaz:
http://arxiv.org/abs/2404.18101
Support vector regression (SVR) has garnered significant popularity over the past two decades owing to its wide range of applications across various fields. Despite its versatility, SVR encounters challenges when confronted with outliers and noise, p
Externí odkaz:
http://arxiv.org/abs/2401.16785
Support vector machine (SVM) is one of the most studied paradigms in the realm of machine learning for classification and regression problems. It relies on vectorized input data. However, a significant portion of the real-world data exists in matrix
Externí odkaz:
http://arxiv.org/abs/2310.19717
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024
In the domain of machine learning, the significance of the loss function is paramount, especially in supervised learning tasks. It serves as a fundamental pillar that profoundly influences the behavior and efficacy of supervised learning algorithms.
Externí odkaz:
http://arxiv.org/abs/2309.02250
Publikováno v:
In Applied Soft Computing May 2024 157