Memo No . 63 May 26 , 2017 Symmetry Regularization
暂无分享,去创建一个
[1] Charles R. Johnson,et al. Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.
[2] Andrea Tacchetti,et al. Discriminate-and-Rectify Encoders: Learning from Image Transformation Sets , 2017, ArXiv.
[3] Barnabás Póczos,et al. Equivariance Through Parameter-Sharing , 2017, ICML.
[4] Tomaso A. Poggio,et al. When and Why Are Deep Networks Better Than Shallow Ones? , 2017, AAAI.
[5] Max Welling,et al. Steerable CNNs , 2016, ICLR.
[6] Fabio Anselmi,et al. Visual Cortex and Deep Networks: Learning Invariant Representations , 2016 .
[7] Lorenzo Rosasco,et al. Unsupervised learning of invariant representations , 2016, Theor. Comput. Sci..
[8] Max Welling,et al. Group Equivariant Convolutional Networks , 2016, ICML.
[9] Koray Kavukcuoglu,et al. Exploiting Cyclic Symmetry in Convolutional Neural Networks , 2016, ICML.
[10] Stéphane Mallat,et al. Understanding deep convolutional networks , 2016, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.
[11] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[12] Babak Hassibi,et al. Group Frames With Few Distinct Inner Products and Low Coherence , 2015, IEEE Transactions on Signal Processing.
[13] Andrew Zisserman,et al. Spatial Transformer Networks , 2015, NIPS.
[14] Lorenzo Rosasco,et al. On Invariance and Selectivity in Representation Learning , 2015, ArXiv.
[15] Andrea Vedaldi,et al. Understanding Image Representations by Measuring Their Equivariance and Equivalence , 2014, International Journal of Computer Vision.
[16] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[17] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[18] Lorenzo Rosasco,et al. Discriminative template learning in group-convolutional networks for invariant speech representations , 2015, INTERSPEECH.
[19] Andre Martins,et al. Orbit Regularization , 2014, NIPS.
[20] Pedro M. Domingos,et al. Deep Symmetry Networks , 2014, NIPS.
[21] Stefano Soatto,et al. Visual Representations: Defining Properties and Deep Approximations , 2014, ICLR 2016.
[22] László Tóth,et al. Combining time- and frequency-domain convolution in convolutional neural network-based phone recognition , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[23] Max Welling,et al. Learning the Irreducible Representations of Commutative Lie Groups , 2014, ICML.
[24] Learning to relate images. , 2013, IEEE transactions on pattern analysis and machine intelligence.
[25] Stéphane Mallat,et al. Rotation, Scaling and Deformation Invariant Scattering for Texture Discrimination , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[26] Joan Bruna,et al. Learning Stable Group Invariant Representations with Convolutional Networks , 2013, ICLR.
[27] Pascal Vincent,et al. Representation Learning: A Review and New Perspectives , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[28] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[29] Honglak Lee,et al. Learning Invariant Representations with Local Transformations , 2012, ICML.
[30] S. Mallat,et al. Invariant Scattering Convolution Networks , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[31] Stefano Soatto,et al. Steps Towards a Theory of Visual Information: Active Perception, Signal-to-Symbol Conversion and the Interplay Between Sensing and Control , 2011, ArXiv.
[32] Honglak Lee,et al. Unsupervised learning of hierarchical representations with convolutional deep belief networks , 2011, Commun. ACM.
[33] Christopher K. I. Williams,et al. Transformation Equivariant Boltzmann Machines , 2011, ICANN.
[34] Jürgen Schmidhuber,et al. Stacked Convolutional Auto-Encoders for Hierarchical Feature Extraction , 2011, ICANN.
[35] Geoffrey E. Hinton,et al. Transforming Auto-Encoders , 2011, ICANN.
[36] Bruno A. Olshausen,et al. Lie Group Transformation Models for Predictive Video Coding , 2011, 2011 Data Compression Conference.
[37] Pascal Frossard,et al. Dictionary Learning , 2011, IEEE Signal Processing Magazine.
[38] Quoc V. Le,et al. Tiled convolutional neural networks , 2010, NIPS.
[39] Bruno A. Olshausen,et al. An Unsupervised Algorithm For Learning Lie Group Transformations , 2010, ArXiv.
[40] R. Fergus,et al. Learning invariant features through topographic filter maps , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[41] João M. F. Xavier,et al. ANSIG—An analytic signature for permutation-invariant two-dimensional shape representation , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[42] Calyampudi R. Rao. Theory of Statistical Inference , 2008 .
[43] Shayne Waldron,et al. Tight frames generated by finite nonabelian groups , 2008, Numerical Algorithms.
[44] B. D. Johnson,et al. Frame potential and finite abelian groups , 2008, 0801.3813.
[45] Rajesh P. N. Rao,et al. Learning the Lie Groups of Visual Invariance , 2007, Neural Computation.
[46] Shift-Invariance Sparse Coding for Audio Classification , 2007, UAI.
[47] Hans Burkhardt,et al. Invariant kernel functions for pattern analysis and machine learning , 2007, Machine Learning.
[48] Thomas Serre,et al. Robust Object Recognition with Cortex-Like Mechanisms , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[49] Yoshua. Bengio,et al. Learning Deep Architectures for AI , 2007, Found. Trends Mach. Learn..
[50] Pierre Vandergheynst,et al. MoTIF: An Efficient Algorithm for Learning Translation Invariant Dictionaries , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.
[51] Thomas Strohmer,et al. GRASSMANNIAN FRAMES WITH APPLICATIONS TO CODING AND COMMUNICATION , 2003, math/0301135.
[52] Yonina C. Eldar,et al. Geometrically uniform frames , 2001, IEEE Trans. Inf. Theory.
[53] Michael I. Jordan,et al. Distance Metric Learning with Application to Clustering with Side-Information , 2002, NIPS.
[54] Xiaoming Huo,et al. Uncertainty principles and ideal atomic decomposition , 2001, IEEE Trans. Inf. Theory.
[55] Rajesh P. N. Rao,et al. Learning Lie Groups for Invariant Visual Perception , 1998, NIPS.
[56] Yaser S. Abu-Mostafa,et al. Hints and the VC Dimension , 1993, Neural Computation.
[57] Geoffrey E. Hinton,et al. Learning symmetry groups with hidden units: beyond the perceptron , 1986 .
[58] D. Slepian. Group codes for the Gaussian channel , 1968 .
[59] A. Cayley,et al. VII. On the theory of groups as depending on the symbolic equation θn = 1.—Part III , 1854 .