20 Result(s)
within
English
Control, Robotics, Mechatronics
Shitong **ang
Article
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Article
Deep adversarial reconstruction classification network for unsupervised domain adaptation
Although the existing adversarial domain adaptation methods have been successfully applied in the unsupervised domain adaptation community, their performances may perhaps be weakened due to a significant distr...
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A novel data-free continual learning method with contrastive reversion
While continual learning has shown its impressive performance in addressing catastrophic forgetting of traditional neural networks and enabling them to learn multiple tasks continuously, it still requires a la...
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Self-paced and Bayes-decision-rule linear KNN prediction
While a testing sample may be first encoded linearly with labeled samples and then classified with KNN on the sum of the obtained weights of the samples in each class so as to avoid the consistent distribution...
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A fuzzy system with common linear-term consequents equivalent to FLNN and GMM
In this study, a novel Takagi–Sugeno–Kang (TSK) fuzzy system termed as CLT–TSK in which the consequent of each fuzzy rule owns a common linear term is exploited to demonstrate its four distinctive merits. They ar...
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Multi-view local linear KNN classification: theoretical and experimental studies on image classification
When handling special multi-view scenarios where data from each view keep the same features, we may perhaps encounter two serious challenges: (1) samples from different views of the same class are less similar...
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Extreme vector machine for fast training on large data
Quite often, different types of loss functions are adopted in SVM or its variants to meet practical requirements. How to scale up the corresponding SVMs for large datasets are becoming more and more important ...
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v-soft margin multi-task learning logistic regression
Coordinate descent (CD) is an effective method for large scale classification problems with simple operations and fast convergence speed. In this paper, inspired by v-soft margin support vector machine and multi-...
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Generalized competitive agglomeration clustering algorithm
In this paper, a generalized competitive agglomeration (CA) clustering algorithm called entropy index constraints competitive agglomeration (EICCA) is proposed to avoid the drawback that the fuzziness index m in ...
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Incremental enhanced α-expansion move for large data: a probability regularization perspective
To deal with large data clustering tasks, an incremental version of exemplar-based clustering algorithm is proposed in this paper. The novel clustering algorithm, called Incremental Enhanced α-Expansion Move (IEE...
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Nonnegative matrix factorization with manifold regularization and maximum discriminant information
Nonnegative matrix factorization (NMF) has been successfully used in different applications including computer vision, pattern recognition and text mining. NMF aims to decompose a data matrix into the product ...
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Privacy preserving and fast decision for novelty detection using support vector data description
Support vector data description (SVDD) has been widely used in novelty detection applications. Since the decision function of SVDD is expressed through the support vectors which contain sensitive information, ...
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MSAFC: matrix subspace analysis with fuzzy clustering ability
In this paper, based on the maximum margin criterion (MMC) together with the fuzzy clustering and the tensor theory, a novel matrix based fuzzy maximum margin criterion (MFMMC) is proposed and based upon which...
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From Gaussian kernel density estimation to kernel methods
This paper explores how a kind of probabilistic systems, namely, Gaussian kernel density estimation (GKDE), can be used to interpret several classical kernel methods, including the well-known support vector ma...
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Transformation between type-2 TSK fuzzy systems and an uncertain Gaussian mixture model
In this paper, an interval extension of the Gaussian mixture model called uncertain Gaussian mixture model (UGMM) is proposed and its transformation into the additive type-2 TSK fuzzy systems is presented. The...
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An enhanced possibilistic C-Means clustering algorithm EPCM
The possibility based clustering algorithm PCM was first proposed by Krishnapuram and Keller to overcome the noise sensitivity of algorithm FCM (Fuzzy C-Means). However, PCM still suffers from the following we...
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Possibility Theoretic Clustering and its Preliminary Application to Large Image Segmentation
Rooted at the exponential possibility model recently developed by Tanaka and his colleagues, a new clustering criterion or concept is introduced and a possibility theoretic clustering algorithm is proposed. Th...
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Attribute weighted mercer kernel based fuzzy clustering algorithm for general non-spherical datasets
Clustering analysis is an important topic in artificial intelligence, data mining and pattern recognition research. Conventional clustering algorithms, for instance, the famous Fuzzy C-means clustering algorit...
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Clustering Analysis of Gene Expression Data based on Semi-supervised Visual Clustering Algorithm
When gene expression datasets contain some labeled data samples, the labeled information should be incorporated into clustering algorithm such that more reasonable clustering results can be achieved. In this p...
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A novel adaptive SVR based filter ASBF for image restoration
In this paper, a novel adaptive filter ASBF based on support vector regression (SVR) is proposed to preserve more image details and efficiently suppress impulse noise simultaneously. The main idea of the novel...
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Fuzzy inference systems with no any rule base and linearly parameter growth
A class of new fuzzy inference systems New-FISs is presented. Compared with the standard fiazzy system, New-FIS is still a universal approximator and has no fiizzy rule base and linearly parameter growth. Thus...
