Support vector data description (SVDD) is a widely used novelty detection algorithm. It provides excellent predictions even in the absence of negative samples and retains the mathematical elegance of Support Vector Machines. The decision boundary can be very flexible due to the incorporation of kernel...
Pinball loss support vector data description for outlier detection. Appl. Intell. 52, 16940–16961 (2022). Article MATH Google Scholar Zheng, Y. F., Wang, S. Y. & Chen, B. D. Robust one-class classification with support vector data description and mixed exponential loss function. Eng....
Active learning based support vector data description method for robust novelty detection Knowl. Based Syst. (2018) ShiX. et al. Robust principal component analysis via optimal mean by joint ℓ2,1 and Schatten p-norms minimization Neurocomputing (2018) DengC. et al. Active multi-kernel domain...
Local illumination models compute the radiance from local properties—such as the position, normal vector, and material data—in addition to global light source parameters. Each point is shaded independently, which opens up a lot of possibilities for parallel computation. This independent ...
For data sets with more than 5000 examples, a random sample of size 5000 has been drawn to limit the runtime of the experiments. Table 1 gives some statistics on the data sets. 748 S. Ru¨ping Table 1. Description of the data sets used in the experiments Id Name Size Dimension Id ...
By accepting optional cookies, you consent to the processing of your personal data - including transfers to third parties. Some third parties are outside of the European Economic Area, with varying standards of data protection. See our privacy policy for more information on the use of your perso...
Construction of uncertainty set for (μ-SMAD) model using support vector clustering Consider a collection of N data points D={rk}k=1N for uncertain expected return vector where rk=(r1k,…,rnk)′,k=1,…,N. The SVC algorithm (Ben-Hur, Horn, Siegelmann, & Vapnik, 2001) looks for the ...
B. Rao. Rule extraction from linear support vector machines. In Proceedings of The Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining., 2005. 12. Y. Jin and B. Sendhoff. Trade-off between performance and robustness: an evolutionary multiobjective approach, in: ...
Table 2. Statistical description of data used in this study. ParameterMinimumMaximumAverage Dilution ratio (mL/g) 2.3 24.3 12.07955 Temperature (°K) 293 338 312.4318 Molecular weight of solvent (g/mol) 72.15 170.33 116.1417 Amount of asphaltene precipitation (wt%) 0.12 7.06 2.964602 5. Results...
Description: TECHNICAL STATEMENT This invention is related to data storage, and more specifically, to distributed and decentralized data storage techniques. BACKGROUND With advances in computing, such systems are employed in many aspects of communications, industrial control, and industry, in general. As...