A review on advances in deep learning
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[1] Geoffrey E. Hinton. Where Do Features Come From? , 2014, Cogn. Sci..
[2] Jonathan G. Fiscus,et al. Darpa Timit Acoustic-Phonetic Continuous Speech Corpus CD-ROM {TIMIT} | NIST , 1993 .
[3] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[4] Simon J. Doran,et al. Stacked Autoencoders for Unsupervised Feature Learning and Multiple Organ Detection in a Pilot Study Using 4D Patient Data , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[5] JEFFREY WOOD,et al. Invariant pattern recognition: A review , 1996, Pattern Recognit..
[6] Yoshua Bengio,et al. Deep Sparse Rectifier Neural Networks , 2011, AISTATS.
[7] Geoffrey E. Hinton,et al. Reducing the Dimensionality of Data with Neural Networks , 2006, Science.
[8] Joshua D. Lamos-Sweeney. Deep learning using genetic algorithms , 2012 .
[9] Pascal Vincent,et al. Representation Learning: A Review and New Perspectives , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[10] Yoshua Bengio,et al. Knowledge Matters: Importance of Prior Information for Optimization , 2013, J. Mach. Learn. Res..
[11] Tara N. Sainath,et al. Improving deep neural networks for LVCSR using rectified linear units and dropout , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[12] Antanas Verikas,et al. Feature selection with neural networks , 2002, Pattern Recognit. Lett..
[13] Guoqiang Peter Zhang,et al. Neural networks for classification: a survey , 2000, IEEE Trans. Syst. Man Cybern. Part C.
[14] Geoffrey E. Hinton. Learning multiple layers of representation , 2007, Trends in Cognitive Sciences.
[15] James Theiler,et al. Online feature selection for pixel classification , 2005, ICML.
[16] Gerald Penn,et al. Convolutional Neural Networks for Speech Recognition , 2014, IEEE/ACM Transactions on Audio, Speech, and Language Processing.
[17] Pietro Perona,et al. Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.
[18] Michael J. Quinn,et al. Parallel programming in C with MPI and OpenMP , 2003 .
[19] Qiang Chen,et al. Network In Network , 2013, ICLR.
[20] Yoshua Bengio,et al. Convolutional networks for images, speech, and time series , 1998 .
[21] Huai Li,et al. Artificial convolution neural network for medical image pattern recognition , 1995, Neural Networks.
[22] Minyoung Kim,et al. Deep Clustered Convolutional Kernels , 2015, FE@NIPS.
[23] P. N. Suganthan,et al. Differential Evolution: A Survey of the State-of-the-Art , 2011, IEEE Transactions on Evolutionary Computation.
[24] Yoshua Bengio,et al. Evolving Culture Versus Local Minima , 2014, Growing Adaptive Machines.
[25] Yan Wu,et al. A Simulation Study of Deep Belief Network Combined with the Self-Organizing Mechanism of Adaptive Resonance Theory , 2010, 2010 International Conference on Computational Intelligence and Software Engineering.
[26] Andrzej Bargiela,et al. Towards Evolutionary Deep Neural Networks , 2014, ECMS.
[27] Li Fei-Fei,et al. ImageNet: A large-scale hierarchical image database , 2009, CVPR.
[28] Tom V. Mathew. Genetic Algorithm , 2022 .
[29] Tara N. Sainath,et al. Optimization Techniques to Improve Training Speed of Deep Neural Networks for Large Speech Tasks , 2013, IEEE Transactions on Audio, Speech, and Language Processing.
[30] Jürgen Schmidhuber,et al. Multi-column deep neural networks for image classification , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[31] Yoshua Bengio,et al. Understanding the difficulty of training deep feedforward neural networks , 2010, AISTATS.
[32] Quoc V. Le,et al. On optimization methods for deep learning , 2011, ICML.
[33] Yann LeCun,et al. Learning Invariant Feature Hierarchies , 2012, ECCV Workshops.
[34] Iddo Greental,et al. Genetic algorithms for evolving deep neural networks , 2014, GECCO.
[35] James Martens,et al. Deep learning via Hessian-free optimization , 2010, ICML.
[36] Yoshua Bengio,et al. Random Search for Hyper-Parameter Optimization , 2012, J. Mach. Learn. Res..
[37] Rob Fergus,et al. Visualizing and Understanding Convolutional Networks , 2013, ECCV.
[38] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[39] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[40] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[41] Heekuck Oh,et al. Neural Networks for Pattern Recognition , 1993, Adv. Comput..
[42] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[43] Alex Krizhevsky,et al. Learning Multiple Layers of Features from Tiny Images , 2009 .
[44] Kunihiko Fukushima,et al. Neocognitron: A new algorithm for pattern recognition tolerant of deformations and shifts in position , 1982, Pattern Recognit..
[45] Riccardo Poli,et al. Particle swarm optimization , 1995, Swarm Intelligence.
[46] Rong Jin,et al. Online Feature Selection and Its Applications , 2014, IEEE Transactions on Knowledge and Data Engineering.
[47] Wonyong Sung,et al. Fixed point optimization of deep convolutional neural networks for object recognition , 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[48] Tijmen Tieleman,et al. Training restricted Boltzmann machines using approximations to the likelihood gradient , 2008, ICML '08.
[49] Brian Cheung,et al. Hybrid Evolution of Convolutional Networks , 2011, 2011 10th International Conference on Machine Learning and Applications and Workshops.
[50] Satish Kumar Jain,et al. Neural networks : a classroom approach , 2005 .
[51] Marco Dorigo,et al. Ant colony optimization theory: A survey , 2005, Theor. Comput. Sci..
[52] Lukasz A. Kurgan,et al. Neural Networks in Bioinformatics , 2012, Handbook of Natural Computing.
[53] Tara N. Sainath,et al. Deep Convolutional Neural Networks for Large-scale Speech Tasks , 2015, Neural Networks.
[54] Alex Krizhevsky,et al. One weird trick for parallelizing convolutional neural networks , 2014, ArXiv.
[55] T. Hampton,et al. The Cancer Genome Atlas , 2020, Indian Journal of Medical and Paediatric Oncology.
[56] Jürgen Schmidhuber,et al. Deep learning in neural networks: An overview , 2014, Neural Networks.
[57] John Shawe-Taylor,et al. Representation Theory and Invariant Neural Networks , 1996, Discret. Appl. Math..
[58] Yoshua Bengio,et al. Deep Learning for NLP (without Magic) , 2012, ACL.
[59] Huan Liu,et al. Feature Selection for Classification , 1997, Intell. Data Anal..
[60] Giovanni Montana,et al. Deep neural networks for anatomical brain segmentation , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[61] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[62] D. Hubel,et al. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex , 1962, The Journal of physiology.
[63] Goldberg,et al. Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.
[64] Jack Dongarra,et al. PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing , 1995 .
[65] Lawrence D. Jackel,et al. Backpropagation Applied to Handwritten Zip Code Recognition , 1989, Neural Computation.
[66] Marc'Aurelio Ranzato,et al. Large Scale Distributed Deep Networks , 2012, NIPS.
[67] Yann LeCun,et al. The mnist database of handwritten digits , 2005 .
[68] Geoffrey E. Hinton,et al. Application of Deep Belief Networks for Natural Language Understanding , 2014, IEEE/ACM Transactions on Audio, Speech, and Language Processing.
[69] Yaroslav Bulatov,et al. Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks , 2013, ICLR.
[70] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[71] Anil K. Jain,et al. Feature extraction methods for character recognition-A survey , 1996, Pattern Recognit..
[72] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[73] Tara N. Sainath,et al. FUNDAMENTAL TECHNOLOGIES IN MODERN SPEECH RECOGNITION Digital Object Identifier 10.1109/MSP.2012.2205597 , 2012 .
[74] Manuel López-Ibáñez,et al. Ant colony optimization , 2010, GECCO '10.
[75] Miguel Torres,et al. Feature Selection Using Artificial Neural Networks , 2008, MICAI.
[76] Honglak Lee,et al. Unsupervised learning of hierarchical representations with convolutional deep belief networks , 2011, Commun. ACM.
[77] Yoshua Bengio,et al. Gradient Flow in Recurrent Nets: the Difficulty of Learning Long-Term Dependencies , 2001 .