Zobrazeno 1 - 10
of 327
pro vyhledávání: '"Shao Yuan-hai"'
Learning using statistical invariants (LUSI) is a new learning paradigm, which adopts weak convergence mechanism, and can be applied to a wider range of classification problems. However, the computation cost of invariant matrices in LUSI is high for
Externí odkaz:
http://arxiv.org/abs/2403.20122
In this paper, we propose a new way of remembering by introducing a memory influence mechanism for the least squares support vector machine (LSSVM). Without changing the equation constraints of the original LSSVM, this mechanism, allows an accurate p
Externí odkaz:
http://arxiv.org/abs/2308.16456
Autor:
Zhu, Meng-Xian, Shao, Yuan-Hai
In this paper, we study the classification problem by estimating the conditional probability function of the given data. Different from the traditional expected risk estimation theory on empirical data, we calculate the probability via Fredholm equat
Externí odkaz:
http://arxiv.org/abs/2210.05953
Autor:
Wang, Zhen, Shao, Yuan-Hai
Publikováno v:
Pattern Recognition, 2024
Classifying the training data correctly without over-fitting is one of the goals in machine learning. In this paper, we propose a generalization-memorization mechanism, including a generalization-memorization decision and a memory modeling principle.
Externí odkaz:
http://arxiv.org/abs/2207.03976
Publikováno v:
In Information Sciences January 2025 689
Recent advance on linear support vector machine with the 0-1 soft margin loss ($L_{0/1}$-SVM) shows that the 0-1 loss problem can be solved directly. However, its theoretical and algorithmic requirements restrict us extending the linear solving frame
Externí odkaz:
http://arxiv.org/abs/2203.00399
Publikováno v:
In Pattern Recognition September 2024 153
Publikováno v:
In Information Sciences May 2024 667
Publikováno v:
IEEE Transactions on Fuzzy Systems, 2021
In semi-supervised fuzzy clustering, this paper extends the traditional pairwise constraint (i.e., must-link or cannot-link) to fuzzy pairwise constraint. The fuzzy pairwise constraint allows a supervisor to provide the grade of similarity or dissimi
Externí odkaz:
http://arxiv.org/abs/2104.08546
Recently proposed L2-norm linear discriminant analysis criterion via the Bhattacharyya error bound estimation (L2BLDA) is an effective improvement of linear discriminant analysis (LDA) for feature extraction. However, L2BLDA is only proposed to cope
Externí odkaz:
http://arxiv.org/abs/2011.05507