Kernel-based Graph Convolutional Networks
暂无分享,去创建一个
[1] Yixin Chen,et al. An End-to-End Deep Learning Architecture for Graph Classification , 2018, AAAI.
[2] G. Wahba,et al. A Correspondence Between Bayesian Estimation on Stochastic Processes and Smoothing by Splines , 1970 .
[3] Nello Cristianini,et al. Kernel Methods for Pattern Analysis , 2003, ICTAI.
[4] Le Song,et al. Scalable Kernel Methods via Doubly Stochastic Gradients , 2014, NIPS.
[5] Andrew Zisserman,et al. Efficient additive kernels via explicit feature maps , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[6] Joan Bruna,et al. Spectral Networks and Locally Connected Networks on Graphs , 2013, ICLR.
[7] Dennis DeCoste,et al. Compact Random Feature Maps , 2013, ICML.
[8] Hichem Sahbi,et al. High Order Stochastic Graphlet Embedding for Graph-Based Pattern Recognition , 2017, ArXiv.
[9] Hichem Sahbi. ImageCLEF annotation with explicit context-aware kernel maps , 2015, International Journal of Multimedia Information Retrieval.
[10] Bernhard Schölkopf,et al. Improving the Accuracy and Speed of Support Vector Machines , 1996, NIPS.
[11] Jure Leskovec,et al. Hierarchical Graph Representation Learning with Differentiable Pooling , 2018, NeurIPS.
[12] Mooi Choo Chuah,et al. Category-Blind Human Action Recognition: A Practical Recognition System , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[13] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[14] Hichem Sahbi,et al. A particular Gaussian mixture model for clustering and its application to image retrieval , 2008, Soft Comput..
[15] F. Scarselli,et al. A new model for learning in graph domains , 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..
[16] Hichem Sahbi,et al. Transductive Kernel Map Learning and Its Application Image Annotation , 2012, BMVC.
[17] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[18] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[19] Le Song,et al. Stochastic Training of Graph Convolutional Networks with Variance Reduction , 2017, ICML.
[20] Richard S. Zemel,et al. Gated Graph Sequence Neural Networks , 2015, ICLR.
[21] Ah Chung Tsoi,et al. The Graph Neural Network Model , 2009, IEEE Transactions on Neural Networks.
[22] Hichem Sahbi,et al. Deep Temporal Pyramid Design for Action Recognition , 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[23] Le Song,et al. Learning Steady-States of Iterative Algorithms over Graphs , 2018, ICML.
[24] Junzhou Huang,et al. Adaptive Sampling Towards Fast Graph Representation Learning , 2018, NeurIPS.
[25] Forrest N. Iandola,et al. SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <1MB model size , 2016, ArXiv.
[26] Davide Bacciu,et al. Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing , 2018, ICML.
[27] Gang Wang,et al. Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition , 2016, ECCV.
[28] Nanning Zheng,et al. View Adaptive Recurrent Neural Networks for High Performance Human Action Recognition from Skeleton Data , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[29] F. Fleuret,et al. Scale-Invariance of Support Vector Machines based on the Triangular Kernel , 2001 .
[30] Bo Chen,et al. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications , 2017, ArXiv.
[31] Max Welling,et al. Variational Graph Auto-Encoders , 2016, ArXiv.
[32] Alexander J. Smola,et al. Fastfood: Approximate Kernel Expansions in Loglinear Time , 2014, ArXiv.
[33] Harish Karnick,et al. Random Feature Maps for Dot Product Kernels , 2012, AISTATS.
[34] Jonathan Masci,et al. Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[35] Ruoyu Li,et al. Adaptive Graph Convolutional Neural Networks , 2018, AAAI.
[36] Xavier Bresson,et al. Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering , 2016, NIPS.
[37] Xiaohui Xie,et al. Co-Occurrence Feature Learning for Skeleton Based Action Recognition Using Regularized Deep LSTM Networks , 2016, AAAI.
[38] Hichem Sahbi,et al. Kernel methods and scale invariance using the triangular kernel , 2004 .
[39] Subhransu Maji,et al. Efficient Classification for Additive Kernel SVMs , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[40] Cao Xiao,et al. FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling , 2018, ICLR.
[41] Philip S. Yu,et al. A Comprehensive Survey on Graph Neural Networks , 2019, IEEE Transactions on Neural Networks and Learning Systems.
[42] Donald F. Towsley,et al. Diffusion-Convolutional Neural Networks , 2015, NIPS.
[43] Lorenzo Livi,et al. Graph Neural Networks With Convolutional ARMA Filters , 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[44] Brian Kingsbury,et al. How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets , 2014, ArXiv.
[45] Yong Du,et al. Hierarchical recurrent neural network for skeleton based action recognition , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[46] Gang Wang,et al. NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[47] King-Sun Fu,et al. IEEE Transactions on Pattern Analysis and Machine Intelligence Publication Information , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[48] Xiaolong Li,et al. GeniePath: Graph Neural Networks with Adaptive Receptive Paths , 2018, AAAI.
[49] Ethem Alpaydin,et al. Multiple Kernel Learning Algorithms , 2011, J. Mach. Learn. Res..
[50] Gang Wang,et al. Skeleton-Based Human Action Recognition With Global Context-Aware Attention LSTM Networks , 2017, IEEE Transactions on Image Processing.
[51] Marc G. Genton,et al. Classes of Kernels for Machine Learning: A Statistics Perspective , 2002, J. Mach. Learn. Res..
[52] Vladimir Vapnik,et al. An overview of statistical learning theory , 1999, IEEE Trans. Neural Networks.
[53] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[54] Qiang Ma,et al. Dual Graph Convolutional Networks for Graph-Based Semi-Supervised Classification , 2018, WWW.
[55] Christian Wolf,et al. Pose-conditioned Spatio-Temporal Attention for Human Action Recognition , 2017, ArXiv.
[56] Wenjun Zeng,et al. An End-to-End Spatio-Temporal Attention Model for Human Action Recognition from Skeleton Data , 2016, AAAI.
[57] Alessio Micheli,et al. Neural Network for Graphs: A Contextual Constructive Approach , 2009, IEEE Transactions on Neural Networks.
[58] Stefano Berretti,et al. A Novel Geometric Framework on Gram Matrix Trajectories for Human Behavior Understanding , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[59] Mehryar Mohri,et al. Learning Non-Linear Combinations of Kernels , 2009, NIPS.
[60] Quentin Oliveau,et al. Learning Attribute Representations for Remote Sensing Ship Category Classification , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[61] Zhengyang Wang,et al. Large-Scale Learnable Graph Convolutional Networks , 2018, KDD.
[62] Jure Leskovec,et al. Inductive Representation Learning on Large Graphs , 2017, NIPS.
[63] Joseph J. LaViola,et al. DeepGRU: Deep Gesture Recognition Utility , 2018, ISVC.
[64] Xavier Bresson,et al. CayleyNets: Graph Convolutional Neural Networks With Complex Rational Spectral Filters , 2017, IEEE Transactions on Signal Processing.
[65] Mathias Niepert,et al. Learning Convolutional Neural Networks for Graphs , 2016, ICML.
[66] Joan Bruna,et al. Deep Convolutional Networks on Graph-Structured Data , 2015, ArXiv.
[67] Kilian Q. Weinberger,et al. Simplifying Graph Convolutional Networks , 2019, ICML.
[68] Hong Cheng,et al. Interactive body part contrast mining for human interaction recognition , 2014, 2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW).
[69] Lawrence K. Saul,et al. Kernel Methods for Deep Learning , 2009, NIPS.
[70] Hichem Sahbi,et al. Deep kernel map networks for image annotation , 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[71] Jure Leskovec,et al. How Powerful are Graph Neural Networks? , 2018, ICLR.
[72] Max Welling,et al. Semi-Supervised Classification with Graph Convolutional Networks , 2016, ICLR.
[73] Hichem Sahbi,et al. Semi supervised deep kernel design for image annotation , 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[74] Benjamin Recht,et al. Random Features for Large-Scale Kernel Machines , 2007, NIPS.
[75] Bernhard Schölkopf,et al. A Generalized Representer Theorem , 2001, COLT/EuroCOLT.
[76] Hao Ma,et al. GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs , 2018, UAI.
[77] Hichem Sahbi,et al. From coarse to fine skin and face detection , 2000, ACM Multimedia.