Deep multiple multilayer kernel learning in core vector machines
暂无分享,去创建一个
[1] Jacek M. Zurada,et al. Generalized Core Vector Machines , 2006, IEEE Transactions on Neural Networks.
[2] Andrzej Cichocki,et al. Kernel PCA for Feature Extraction and De-Noising in Nonlinear Regression , 2001, Neural Computing & Applications.
[3] Yong Du,et al. Hierarchical recurrent neural network for skeleton based action recognition , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[4] Andrew Gordon Wilson,et al. Deep Kernel Learning , 2015, AISTATS.
[5] Erik Marchi,et al. Sparse Autoencoder-Based Feature Transfer Learning for Speech Emotion Recognition , 2013, 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction.
[6] Geoffrey E. Hinton,et al. Deep Boltzmann Machines , 2009, AISTATS.
[7] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[8] Pascal Vincent,et al. Representation Learning: A Review and New Perspectives , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[9] Lawrence K. Saul,et al. Analysis and Extension of Arc-Cosine Kernels for Large Margin Classification , 2011, ArXiv.
[10] Yoshua. Bengio,et al. Learning Deep Architectures for AI , 2007, Found. Trends Mach. Learn..
[11] Yoshua Bengio,et al. Greedy Layer-Wise Training of Deep Networks , 2006, NIPS.
[12] M. Narasimha Murty,et al. Cluster Based Core Vector Machine , 2006, Sixth International Conference on Data Mining (ICDM'06).
[13] Lawrence K. Saul,et al. Kernel Methods for Deep Learning , 2009, NIPS.
[14] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[15] Phil Blunsom,et al. A Convolutional Neural Network for Modelling Sentences , 2014, ACL.
[16] Ivor W. Tsang,et al. Core Vector Machines: Fast SVM Training on Very Large Data Sets , 2005, J. Mach. Learn. Res..
[17] Ah Chung Tsoi,et al. Face recognition: a convolutional neural-network approach , 1997, IEEE Trans. Neural Networks.
[18] Walid Mahdi,et al. Deep multilayer multiple kernel learning , 2016, Neural Computing and Applications.
[19] Shiliang Sun,et al. Multitask multiclass support vector machines: Model and experiments , 2013, Pattern Recognit..
[20] S. Asharaf,et al. Deep kernel learning in core vector machines , 2017, Pattern Analysis and Applications.
[21] Steven C. H. Hoi,et al. Unsupervised Multiple Kernel Learning , 2011, ACML.
[22] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[23] Marc'Aurelio Ranzato,et al. Efficient Learning of Sparse Representations with an Energy-Based Model , 2006, NIPS.
[24] Florian Metze,et al. Deep maxout networks for low-resource speech recognition , 2013, 2013 IEEE Workshop on Automatic Speech Recognition and Understanding.
[25] Geoffrey E. Hinton. Learning multiple layers of representation , 2007, Trends in Cognitive Sciences.
[26] Y. Liu,et al. Bilinear deep learning for image classification , 2011, ACM Multimedia.
[27] M. Narasimha Murty,et al. Multiclass core vector machine , 2007, ICML '07.
[28] Tara N. Sainath,et al. Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups , 2012, IEEE Signal Processing Magazine.
[29] Honglak Lee,et al. Sparse deep belief net model for visual area V2 , 2007, NIPS.
[30] Michael I. Jordan,et al. Multiple kernel learning, conic duality, and the SMO algorithm , 2004, ICML.
[31] Honglak Lee,et al. Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations , 2009, ICML '09.
[32] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..