Efficient and Rapid Machine Learning Algorithms for Big Data and Dynamic Varying Systems

IEEE Transactions on Systems, Man, and Cybernetics: Systems

Volumn 47, Issue 10, 2017, Pages 2625-2626

  Sun, Fuchun ^a   Huang, Guang Bin ^b   Jonathan Wu, Q M ^c   Song, Shiji ^a   Wunsch, Donald C ^d  

^a TSINGHUA UNIVERSITY   (China)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^c UNIVERSITY OF WINDSOR   (Canada)

^d MISSOURI UNIVERSITY OF SCIENCE AND TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIG DATA; LEARNING SYSTEMS;

COMPUTATIONAL INTELLIGENCE TECHNIQUES; CONVERGENCE TIME; EXPONENTIAL GROWTH; FAST IMPLEMENTATION; HUMAN INTERVENTION; LATEST DEVELOPMENT; MACHINE LEARNING TECHNIQUES; RESEARCH CHALLENGES;

LEARNING ALGORITHMS;

EID: 85029167518     PISSN: 21682216     EISSN: 21682232     Source Type: Journal    
DOI: 10.1109/TSMC.2017.2741558     Document Type: Article

References (14)

1. C. L. P. Chen and C.-Y. Zhang, "Data-intensive applications, challenges, techniques and technologies: A survey on big data," Inf. Sci., vol. 275, pp. 314-347, Aug. 2014.
2. T. Bodnar, M. L. Dering, C. Tucker, and K. M. Hopkinson, "Using largescale social media networks as a scalable sensing system for modeling real-time energy utilization patterns," IEEE Trans. Syst., Man, Cybern., Syst., vol. 47, no. 10, pp. 2627-2640, Oct. 2017.
3. N. Passalis and A. Tefas, "Learning neural bag-of-features for large-scale image retrieval," IEEE Trans. Syst., Man, Cybern., Syst., vol. 47, no. 10, pp. 2641-2652, Oct. 2017.
4. M. Sharma, Jayadeva, S. Soman, and H. Pant, "Large-scale minimal complexity machines using explicit feature maps," IEEE Trans. Syst., Man, Cybern., Syst., vol. 47, no. 10, pp. 2653-2662, Oct. 2017.
5. X. Song, X. Xia, and F. Luan, "Online signature verification based on stable features extracted dynamically," IEEE Trans. Syst., Man, Cybern., Syst., vol. 47, no. 10, pp. 2663-2676, Oct. 2017.
6. J. Wang, D. Yang, W. Jiang, and J. Zhou, "Semisupervised incremental support vector machine learning based on neighborhood kernel estimation," IEEE Trans. Syst., Man, Cybern., Syst., vol. 47, no. 10, pp. 2677-2687, Oct. 2017.
7. A. Sharabiani et al., "Efficient classification of long time series by 3-D dynamic time warping," IEEE Trans. Syst., Man, Cybern., Syst., vol. 47, no. 10, pp. 2688-2703, Oct. 2017.
8. K. Huang, Q. Zhang, C. Zhou, N. Xiong, and Y. Qin, "An efficient intrusion detection approach for visual sensor networks based on traffic pattern learning," IEEE Trans. Syst., Man, Cybern., Syst., vol. 47, no. 10, pp. 2704-2713, Oct. 2017.
9. L. Bu, D. Zhao, and C. Alippi, "An incremental change detection test based on density difference estimation," IEEE Trans. Syst., Man, Cybern., Syst., vol. 47, no. 10, pp. 2714-2726, Oct. 2017.
10. S. Ramírez-Gallego et al., "Nearest neighbor classification for high-speed big data streams using spark," IEEE Trans. Syst., Man, Cybern., Syst., vol. 47, no. 10, pp. 2727-2739, Oct. 2017.
11. C. Chen, K. Li, A. Ouyang, Z. Tang, and K. Li, "GPU-accelerated parallel hierarchical extreme learning machine on Flink for big data," IEEE Trans. Syst., Man, Cybern., Syst., vol. 47, no. 10, pp. 2740-2753, Oct. 2017.
12. L. Oneto et al., "Dynamic delay predictions for large-scale railway networks: Deep and shallow extreme learning machines tuned via thresholdout," IEEE Trans. Syst., Man, Cybern., Syst., vol. 47, no. 10, pp. 2754-2767, Oct. 2017.
13. L. Carafoli, F. Mandreoli, R. Martoglia, and W. Penzo, "Streaming tables: Native support to streaming data in DBMSs," IEEE Trans. Syst., Man, Cybern., Syst., vol. 47, no. 10, pp. 2768-2782, Oct. 2017.
14. Z.-G. Liu, Q. Pan, J. Dezert, and G. Mercier, "Hybrid classification system for uncertain data," IEEE Trans. Syst., Man, Cybern., Syst., vol. 47, no. 10, pp. 2783-2790, Oct. 2017.