Conditional Generative Moment-Matching Networks
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[1] Yoram Singer,et al. Pegasos: primal estimated sub-gradient solver for SVM , 2011, Math. Program..
[2] Thomas Brox,et al. Learning to Generate Chairs, Tables and Cars with Convolutional Networks , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[3] Geoffrey E. Hinton,et al. Rectified Linear Units Improve Restricted Boltzmann Machines , 2010, ICML.
[4] Ryan P. Adams,et al. Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks , 2015, ICML.
[5] Samy Bengio,et al. Show and tell: A neural image caption generator , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[6] Pedro M. Domingos,et al. Sum-product networks: A new deep architecture , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).
[7] Honglak Lee,et al. Attribute2Image: Conditional Image Generation from Visual Attributes , 2015, ECCV.
[8] Rob Fergus,et al. Stochastic Pooling for Regularization of Deep Convolutional Neural Networks , 2013, ICLR.
[9] Zoubin Ghahramani,et al. Training generative neural networks via Maximum Mean Discrepancy optimization , 2015, UAI.
[10] Yoshua Bengio,et al. Maxout Networks , 2013, ICML.
[11] Zhuowen Tu,et al. Deeply-Supervised Nets , 2014, AISTATS.
[12] Le Song,et al. A Hilbert Space Embedding for Distributions , 2007, Discovery Science.
[13] Nitish Srivastava,et al. Multimodal learning with deep Boltzmann machines , 2012, J. Mach. Learn. Res..
[14] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[15] Michael Rabadi,et al. Kernel Methods for Machine Learning , 2015 .
[16] Masashi Sugiyama,et al. Bayesian Dark Knowledge , 2015 .
[17] Richard S. Zemel,et al. Generative Moment Matching Networks , 2015, ICML.
[18] Andrew McCallum,et al. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.
[19] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[20] Pedro M. Domingos,et al. Discriminative Learning of Sum-Product Networks , 2012, NIPS.
[21] Michael I. Jordan,et al. On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes , 2001, NIPS.
[22] Yuxiao Hu,et al. Face recognition using Laplacianfaces , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[23] Alexander J. Smola,et al. Hilbert space embeddings of conditional distributions with applications to dynamical systems , 2009, ICML '09.
[24] Qiang Chen,et al. Network In Network , 2013, ICLR.
[25] Thomas Brox,et al. Learning to generate chairs with convolutional neural networks , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[26] Yann LeCun,et al. Convolutional neural networks applied to house numbers digit classification , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).
[27] Simon Osindero,et al. Conditional Generative Adversarial Nets , 2014, ArXiv.
[28] Bernhard Schölkopf,et al. A Kernel Two-Sample Test , 2012, J. Mach. Learn. Res..
[29] Bo Zhang,et al. Max-Margin Deep Generative Models , 2015, NIPS.
[30] O. Kallenberg. Foundations of Modern Probability , 2021, Probability Theory and Stochastic Modelling.
[31] Rob Fergus,et al. Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks , 2015, NIPS.
[32] Honglak Lee,et al. Learning Structured Output Representation using Deep Conditional Generative Models , 2015, NIPS.
[33] Le Song,et al. A Hilbert Space Embedding for Distributions , 2007, IFIP Working Conference on Database Semantics.