Clustering Positive Definite Matrices by Learning Information Divergences
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Vassilios Morellas | Anoop Cherian | Panagiotis Stanitsas | Nikolaos Papanikolopoulos | N. Papanikolopoulos | V. Morellas | A. Cherian | P. Stanitsas
[1] René Vidal,et al. Kernel sparse subspace clustering , 2014, 2014 IEEE International Conference on Image Processing (ICIP).
[2] J. Lafferty. Additive models, boosting, and inference for generalized divergences , 1999, COLT '99.
[3] Geoffrey E. Hinton,et al. Stochastic Neighbor Embedding , 2002, NIPS.
[4] Lei Wang,et al. Beyond Covariance: Feature Representation with Nonlinear Kernel Matrices , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[5] Anoop Cherian,et al. Jensen-Bregman LogDet Divergence with Application to Efficient Similarity Search for Covariance Matrices , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[6] Maher Moakher,et al. Symmetric Positive-Definite Matrices: From Geometry to Applications and Visualization , 2006, Visualization and Processing of Tensor Fields.
[7] Cristian Sminchisescu,et al. Semantic Segmentation with Second-Order Pooling , 2012, ECCV.
[8] G. Borgefors,et al. Segmentation of virus particle candidates in transmission electron microscopy images , 2012, Journal of microscopy.
[9] Shun-ichi Amari,et al. Methods of information geometry , 2000 .
[10] Vassilios Morellas,et al. Bayesian Nonparametric Clustering for Positive Definite Matrices , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[11] Junbin Gao,et al. Kernel Sparse Subspace Clustering on Symmetric Positive Definite Manifolds , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[12] René Vidal,et al. Clustering and dimensionality reduction on Riemannian manifolds , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[13] Vassilios Morellas,et al. Active convolutional neural networks for cancerous tissue recognition , 2017, 2017 IEEE International Conference on Image Processing (ICIP).
[14] Xavier Pennec,et al. A Riemannian Framework for Tensor Computing , 2005, International Journal of Computer Vision.
[15] Matti Pietikäinen,et al. A comparative study of texture measures with classification based on featured distributions , 1996, Pattern Recognit..
[16] Shiguang Shan,et al. Log-Euclidean Metric Learning on Symmetric Positive Definite Manifold with Application to Image Set Classification , 2015, ICML.
[17] Mihoko Minami,et al. Robust Blind Source Separation by Beta Divergence , 2002, Neural Computation.
[18] Cristian Sminchisescu,et al. Matrix Backpropagation for Deep Networks with Structured Layers , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[19] Inderjit S. Dhillon,et al. Learning low-rank kernel matrices , 2006, ICML.
[20] Mehrtash Tafazzoli Harandi,et al. Bregman Divergences for Infinite Dimensional Covariance Matrices , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[21] S T Roweis,et al. Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.
[22] Vassilios Morellas,et al. Learning Discriminative αβ-Divergences for Positive Definite Matrices , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[23] M. C. Jones,et al. Robust and efficient estimation by minimising a density power divergence , 1998 .
[24] Vassilios Morellas,et al. Metric learning for semi-supervised clustering of Region Covariance Descriptors , 2009, 2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC).
[25] Sergio Cruces,et al. Log-Determinant Divergences Revisited: Alpha-Beta and Gamma Log-Det Divergences , 2014, Entropy.
[26] Bruno Pelletier. Kernel density estimation on Riemannian manifolds , 2005 .
[27] Mikhail Belkin,et al. Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering , 2001, NIPS.
[28] Fatih Murat Porikli,et al. Region Covariance: A Fast Descriptor for Detection and Classification , 2006, ECCV.
[29] Peter Meer,et al. Nonlinear Mean Shift over Riemannian Manifolds , 2009, International Journal of Computer Vision.
[30] Mehrtash Tafazzoli Harandi,et al. From Manifold to Manifold: Geometry-Aware Dimensionality Reduction for SPD Matrices , 2014, ECCV.
[31] Mehrtash Tafazzoli Harandi,et al. Riemannian coding and dictionary learning: Kernels to the rescue , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[32] Vassilios Morellas,et al. Evaluation of feature descriptors for cancerous tissue recognition , 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).
[33] Andrzej Cichocki,et al. Nonnegative Matrix and Tensor Factorization T , 2007 .
[34] Robert E. Mahony,et al. Optimization Algorithms on Matrix Manifolds , 2007 .
[35] Raul Kompass,et al. A Generalized Divergence Measure for Nonnegative Matrix Factorization , 2007, Neural Computation.
[36] Inderjit S. Dhillon,et al. Generalized Nonnegative Matrix Approximations with Bregman Divergences , 2005, NIPS.
[37] Dario Bini,et al. Computing the Karcher mean of symmetric positive definite matrices , 2013 .
[38] N. Ayache,et al. Log‐Euclidean metrics for fast and simple calculus on diffusion tensors , 2006, Magnetic resonance in medicine.