SVM-based Deep Stacking Networks
@inproceedings{Wang2019SVMbasedDS, title={SVM-based Deep Stacking Networks}, author={Jingyuan Wang and K. Feng and J. Wu}, booktitle={AAAI}, year={2019} }
The deep network model, with the majority built on neural networks, has been proved to be a powerful framework to represent complex data for high performance machine learning. In recent years, more and more studies turn to nonneural network approaches to build diverse deep structures, and the Deep Stacking Network (DSN) model is one of such approaches that uses stacked easy-to-learn blocks to build a parameter-training-parallelizable deep network. In this paper, we propose a novel SVM-based… CONTINUE READING
Figures, Tables, and Topics from this paper
4 Citations
A Kernel Perspective for the Decision Boundary of Deep Neural Networks
- Computer Science
- 2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI)
- 2020
Broad Learning Enhanced 1H-MRS for Early Diagnosis of Neuropsychiatric Systemic Lupus Erythematosus
- Computer Science, Medicine
- Comput. Math. Methods Medicine
- 2020
- Highly Influenced
References
SHOWING 1-10 OF 38 REFERENCES
Tensor Deep Stacking Networks
- Mathematics, Medicine
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- 2013
- 130
- PDF
ImageNet classification with deep convolutional neural networks
- Computer Science
- Commun. ACM
- 2012
- 59,651
- Highly Influential
- PDF
Deep Forest: Towards An Alternative to Deep Neural Networks
- Computer Science
- IJCAI
- 2017
- 427
- Highly Influential
- PDF
Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
- Computer Science, Mathematics
- J. Mach. Learn. Res.
- 2010
- 4,726
- PDF
Deep stacking networks for information retrieval
- Computer Science
- 2013 IEEE International Conference on Acoustics, Speech and Signal Processing
- 2013
- 69
- PDF