Ensembles and Cascading of Embedded Prototype Subspace Classifiers

Deep learning approaches suffer from the so called interpretability problem and can therefore be very hard to visualise. Embedded Prototype Subspace Classifiers is one attempt in the field of expla ...

[1]  D. Opitz,et al.  Popular Ensemble Methods: An Empirical Study , 1999, J. Artif. Intell. Res..

[2]  C. V. Jawahar,et al.  Improving CNN-RNN Hybrid Networks for Handwriting Recognition , 2018, 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR).

[3]  Maya Krishnan,et al.  Against Interpretability: a Critical Examination of the Interpretability Problem in Machine Learning , 2019, Philosophy & Technology.

[4]  Roland Vollgraf,et al.  Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms , 2017, ArXiv.

[5]  T. Kohonen,et al.  Associative recall of images , 2004, Biological Cybernetics.

[6]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[7]  Lior Rokach,et al.  Ensemble-based classifiers , 2010, Artificial Intelligence Review.

[8]  Jaime S. Cardoso,et al.  Machine Learning Interpretability: A Survey on Methods and Metrics , 2019, Electronics.

[9]  T. Kohonen,et al.  The subspace learning algorithm as a formalism for pattern recognition and neural networks , 1988, IEEE 1988 International Conference on Neural Networks.

[10]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Geoffrey E. Hinton,et al.  Visualizing Data using t-SNE , 2008 .

[12]  E. Oja,et al.  Fast adaptive formation of orthogonalizing filters and associative memory in recurrent networks of neuron-like elements , 1976, Biological Cybernetics.

[13]  T. Kohonen,et al.  A principle of neural associative memory , 1977, Neuroscience.

[14]  Anil K. Jain,et al.  Data clustering: a review , 1999, CSUR.

[15]  Rui Xu,et al.  Survey of clustering algorithms , 2005, IEEE Transactions on Neural Networks.

[16]  Gernot A. Fink,et al.  PHOCNet: A Deep Convolutional Neural Network for Word Spotting in Handwritten Documents , 2016, 2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR).

[17]  Mats Lind,et al.  Embedded Prototype Subspace Classification: A Subspace Learning Framework , 2019, CAIP.

[18]  João Gama,et al.  Cascade Generalization , 2000, Machine Learning.

[19]  Heng Tao Shen,et al.  Principal Component Analysis , 2009, Encyclopedia of Biometrics.

[20]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[21]  Larry D. Hostetler,et al.  The estimation of the gradient of a density function, with applications in pattern recognition , 1975, IEEE Trans. Inf. Theory.

[22]  Paul Shapshak Artificial Intelligence and brain , 2018, Bioinformation.

[23]  Francisco Herrera,et al.  Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI , 2020, Inf. Fusion.

[24]  Luc Vincent,et al.  Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  Shigeaki Watanabe,et al.  Subspace method to pattern recognition , 1973 .

[26]  Guang-Zhong Yang,et al.  XAI—Explainable artificial intelligence , 2019, Science Robotics.

[27]  Alex Lamb,et al.  Deep Learning for Classical Japanese Literature , 2018, ArXiv.

[28]  Hans-Peter Kriegel,et al.  A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.

[29]  Gregory Cohen,et al.  EMNIST: an extension of MNIST to handwritten letters , 2017, CVPR 2017.

[30]  Jos B. T. M. Roerdink,et al.  The Watershed Transform: Definitions, Algorithms and Parallelization Strategies , 2000, Fundam. Informaticae.

[31]  Anders Hast,et al.  A short feature vector for image matching: The Log-Polar Magnitude feature descriptor , 2017, PloS one.

[32]  C. V. Jawahar,et al.  Word Spotting and Recognition Using Deep Embedding , 2018, 2018 13th IAPR International Workshop on Document Analysis Systems (DAS).