과제정보
연구 과제번호 : 스마트TV 2.0 소프트웨어 플랫폼
연구 과제 주관 기관 : 정보통신기술진흥센터
참고문헌
- NVIDIA's Next Generation CUDA Compute Architecture: Fermi, v1.1, [Online] Available: http://www.nvidia.com (downloaded 2015, August 21)
- Patel, R., Zhang, Y., Mak, J., Davidson, A., & Owens, J. D., "Parallel lossless data compression on the GPU," Proc. of Innovative Parallel Computing, 2012.
- Huffman, David A., "A method for the construction of minimum redundancy codes," Proc. of the IRE, Vol. 40, No. 9, pp. 1098-1101, 1952.
- Schmidhuber, Jurgen, et al., "Predictive Coding with Neural Nets: Application to Text Compression," Advances in neural information processing systems, pp. 1047-1054. 1995.
- J. Kim, H. Han, "GPGPU-Accelerated Neural Predictive Coding for Text Compression," Proc. of the KIISE Computer Congress, 2015. (in Korean)
- Srivastava, Nitish, et al., "Dropout: A simple way to prevent neural networks from overfitting," The Journal of Machine Learning Research," Vol. 15, No. 1, pp. 1929-1958, 2014.
- Ioffe, Sergey, and Christian Szegedy, "Batch normalization: Accelerating deep network training by reducing internal covariate shift," arXiv preprint arXiv:1502.03167, 2015.
- He, Kaiming, et al., "Delving deep into rectifiers: Surpassing human-level performance on ImageNet classification," Proc. of the IEEE Int'l Conf. on Computer Vision, 2015.
- V. Nair and G.E. Hinton, "Rectified linear units improve restricted boltzmann machines," Proc. of the Int'l Conf. on Machine Learning, 2010.
- Bridle, John S., "Probabilistic interpretation of feedforward classification network outputs, with relationships to statistical pattern recognition," Neurocomputing: Algorithms, Architectures and Applications, Springer, pp. 227-236, 1990.
- Hinton, Geoffrey, Simon Osindero, and Yee-Whye Teh, "A fast learning algorithm for deep belief nets," Neural Computation, Vol. 18, No. 7, pp. 1527-1554, 2006. https://doi.org/10.1162/neco.2006.18.7.1527
- Hochreiter, Sepp and Schmidhuber, Jurgen, "Long Short-Term Memory," Neural Computation, Vol. 9, No. 8, pp. 1735-1780, 1997. https://doi.org/10.1162/neco.1997.9.8.1735
- Sundermeyer, Martin, Ralf Schlüter, and Hermann Ney, "LSTM Neural Networks for Language Modeling," Proc. of the INTERSPEECH, pp. 194-197, 2012.
- Chung, Junyoung, et al., "Empirical evaluation of gated recurrent neural networks on sequence modeling," Poster Presented at Deep Learning and Representation Learning Workshop, 2014.
- Project Gutenberg, Project Gutenberg. [Online]. Availabile: https://www.gutenberg.org/
- Deorowicz, S., "Silesia corpus," Silesian University of Technology, Poland. 2003. [Online]. Available: http://www.data-compression.info/Corpora/SilesiaCorpus/
- Bergstra, James, et al., "Theano: a CPU and GPU math expression compiler," Proc. of the Python for Scientific Computing Conference (SciPy), 2010.
- Francois Chollet. Keras Project [Online]. Available: GitHub Repository, https://github.com/fchollet/keras. 2015.