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D. Y. Plasencia Cala. , Prototype Selection for Classification in Standard and Generalized Dissimilarity Spaces, Ph.D. thesis Delft University of Technology, 2015, September 24, 1-152
D. Porro Munoz, Classification of continuous multi-way data via dissimilarity representation, Ph.D. thesis Delft University of Technology, 2013, October 15, 1-127.
C.V. Dinh, Learning from weakly representative data and applications in spectral image analysis, Ph.D. thesis Delft University of Technology, 2013, October 10, 1-112.
R.P.W. Duin and E. Pekalska, Pattern Recognition: Introduction and Terminology, eBook, 37Steps, 2015, 1-78.
R.P.W. Duin, The origin of patterns, Frontiers in Computer Science, vol. 3, 2021,747195.
R.P.W. Duin, The Dissimilarity Representation for finding Universals from Particulars by an anti-essentialist Approach, Pattern Recognition Letters, vol. 64, 2015, 37-43.
R.C. Wilson, E. Hancock, E. Pekalska, and R.P.W. Duin, Spherical and Hyperbolic Embeddings of Data, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 36, no. 11, 2014, 2255-2269.
O. Rajadell Rojas, P. Garcia-Sevilla, C.V. Dinh, and R.P.W. Duin, Improving hyperspectral pixel classification with unsupervised training selection, Geoscience and Remote Sensing Letters, vol. 11, no. 3, 2014, 656-660.
Y. Plasencia-Calana, M. Orozco-Alzate, E. Garcia-Reyes, and R.P.W. Duin, Selecting feature lines in generalized dissimilarity representations for pattern recognition, Digital Signal Processing, vol. 23, no. 3, 2013, 902-911.
Y. Li, D.M.J. Tax, R.P.W. Duin, and M. Loog, Multiple-instance learning as a classifier combining problem, Pattern Recognition, vol. 46, no. 3, 2013, 865-874.
R. Leitner, M. De Biasio, T. Arnold, C.V. Dinh, M. Loog, and R.P.W. Duin, Multi-spectral video endoscopy system for the detection of cancerous tissue, Pattern Recognition Letters, vol. 34, no. 1, 2013, 85-93.
C.V. Dinh, R.P.W. Duin, I. Piqueras-Salazar, and M. Loog, FIDOS: A generalized Fisher based feature extraction method for domain shift, Pattern Recognition, vol. 49, no. 9, 2013, 2510-2518.
R.P.W. Duin, E. Pekalska, and M. Loog, Non-Euclidean Dissimilarities: Causes, Embedding and Informativeness, in: M. Pelillo (eds.), Similarity-Based Pattern Analysis and Recognition, Advances in Computer Vision and Pattern Recognition, Springer, 2013, 13-44.
Y. Plasencia-Calana, M. Orozco-Alzate, H. Mendez-Vazquez, E. Garcia-Reyes, and R.P.W. Duin, Scalable Prototype Selection by Genetic Algorithms and Hashing, arXiv:1712.09277, 2017, 1-26.
R.P.W. Duin and S. Verzakov, Fast kNN mode seeking clustering applied to active learning, arXiv:1712.07454, 2017, 1-23.
Y. Plasencia-Calana, Y. Li, R.P.W. Duin, M. Orozco Alzate, M. Loog, and E. Garcia-Reyes, A Compact Representation of Multiscale Dissimilarity Data by Prototype Selection, Proc. CIARP 2016, Lecture Notes in Computer Science, Springer, Heidelberg, 2016.
W.J. Lee, D.M.J. Tax, and R.P.W. Duin, Beyond Condition-Monitoring: Comparing Diagnostic Events with Word Sequence Kernel for Train Delay Prediction, Proceedings European Conference of the Prognostic and Health Management Society 2016, 2016.
R.P.W. Duin and E. Pekalska, Zero-error dissimilarity based classifiers, arXiv:1601.04451, 2016, 1-5.
R.P.W. Duin and E. Pekalska, Domain based classification, arXiv:1601.04530, 2016, 1-8.
M. Orozco-Alzate, R.P.W. Duin, and M. Bicego, Unsupervised Parameter Estimation of Non Linear Scaling for Improved Classification in the Dissimilarity Space, Structural, Syntactic, and Statistical Pattern Recognition, Proc. SSSPR 2016, Lecture Notes in Computer Science, vol. 10029, Springer, Heidelberg, 2016, 74-83.
D.M.J. Tax, V. Cheplygina, R.P.W. Duin, and J. van de Poll, The Similarity between Dissimilarities, Structural, Syntactic, and Statistical Pattern Recognition, Proc. SSSPR 2016, Lecture Notes in Computer Science, vol. 10029, Springer, Heidelberg, 2016, 84-94.
Y. Plasencia-Calana, M. Orozco-Alzate, H. Mendez-Vazquez, E. Garcia-Reyes, and R.P.W. Duin, Towards Scalable Prototype Selection by Genetic Algorithms with Fast Criteria, Structural, Syntactic, and Statistical Pattern Recognition, Proc. SSSPR 2014, Lecture Notes in Computer Science, vol. 8621, Springer, Heidelberg, 2014, 343-352.
R.P.W. Duin, M. Bicego, M. Orozco-Alzate, S.W. Kim, and M. Loog, Metric Learning in Dissimilarity Space for Improved Nearest Neighbor Performance, Structural, Syntactic, and Statistical Pattern Recognition, Proc. SSSPR 2014, Lecture Notes in Computer Science, vol. 8621, Springer, Heidelberg, 2014, 183-192.
Y. Plasencia-Calana, V. Cheplygina, R.P.W. Duin, E. Garcia-Reyes, M. Orozco-Alzate, D.M.J. Tax, and M. Loog, On the Informativeness of Asymmetric Dissimilarities, in: E. Hancock, M. Pelillo (eds.), Similarity-Based Pattern Recognition (Proc. Second Int. Workshop, SIMBAD 2013, York, UK), Lecture Notes in Computer Science, vol. 7953, Springer, Berlin, 2013, 75-89.
Y. Plasencia-Calana, M. Orozco-Alzate, E. Garcia-Reyeso, and R.P.W. Duin, Towards cluster- based prototype sets for classification in the dissimilarity space, in: J. Ruiz-Shulcloper and G. Sanniti di Baja (eds.), Proc. CIARP 2013, Part I, Lecture Notes in Computer Science, vol. 8258, Springer, Heidelberg, 2013, 294-301.
Y. Li, D.M.J. Tax, R.P.W. Duin, and M. Loog, The Link between Multiple-Instance Learning and Learning from Only Positive and Unlabelled Examples, Proc. MCS 2013, Lecture Notes in Computer Science, vol. 7872, Springer, Heidelberg, 2013, 157-166.
H. Aidos, A. Fred, and R.P.W. Duin, The area under the ROC curve as a criterion for clustering evaluation, ICPRAM 2013 - Proc. 2nd Int. Conf. on Pattern Recognition Applications and Methods, (Barcelona, Spain, 15-18 Feb., 2013), SciTePress, 2013, 276-280.
D. Porro Munoz, R.P.W. Duin, and I. Talavera, Missing values in dissimilarity-based classification of multi-way data, Proc. CIARP 2013, 2013.