Journal Contributions: Published

Jump to Year:
        2007  2006  2005  2004  2003  2002  2001  2000  1999  1997
      

2007
	F. Angiulli. Condensed Nearest Neighbor Data Domain Description. IEEE Transactions on Pattern Analysis and Machine Intelligence 29:10 (2007) 1746-1758			bib
	F. Angiulli. Fast Nearest Neighbor Condensation for Large Data Sets Classification. IEEE Transactions on Knowledge and Data Engineering 19:11 (2007) 1450-1464			bib
	F. Angiulli, G. Folino. Distributed Nearest Neighbor-Based Condensation of Very Large Data Sets. IEEE Transactions on Knowledge and Data Engineering 19:12 (2007) 1593-1606			bib
	S.W. Kim, B.J. Oommen. On using prototype reduction schemes to optimize dissimilarity-based classification. Pattern Recognition 40 (2007) 2946-2957			bib
2006
	C.H. Chou, C.C. Lin, Y.H. Liu, F. Chang. A prototype classification method and its use in a hybrid solution for multiclass pattern recognition. Pattern Recognition 39 (2006) 624-634			bib
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	D. Huang, T.W.S. Chow. Enhancing density-based data reduction using entropy. Neural Computation 18:2 (2006) 470-495			bib
	S.W. Kim, B.J. Oommen. Prototype reduction schemes applicable for non-stationary data sets. Pattern Recognition 39:2 (2006) 209-222			bib
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	R. Paredes, E. Vidal. Learning prototypes and distances: A prototype reduction technique based on nearest neighbor error minimization. Pattern Recognition 39:2 (2006) 171-179			bib
	E. Pekalska, R.P.W. Duin, P. Paclik. Prototype selection for dissimilarity-based classifiers. Pattern Recognition 39:2 (2006) 189-208			bib
2005
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	J. Li, M.T. Manry, C. Yu, D.R. Wilson. Prototype classifier design with pruning. International Journal on Artificial Intelligence Tools 14:1-2 (2005) 261-280			bib
2004
	S.W. Kim, B.J. Oommen. A Brief Taxonomy and Ranking of Creative Prototype Reduction Schemes. Pattern Analysis and Applications Journal 6:3 (2004) 232-244			bib
	S.W. Kim, B.J. Oommen. On using prototype reduction schemes to optimize kernel-based nonlinear subspace methods. Pattern Recognition 37 (2004) 227-239			bib
	S.W. Kim, B.J. Oommen. Enhancing Prototype Reduction Schemes with Recursion : A Method Applicable for . IEEE Transactions on Systems, Man and Cybernetics, Part B 34:3 (2004) 1384-1397			bib
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2003
	S. Okamoto, N. Yugami. Effects of domain characteristics on instance-based learning algorithm. Theoretical Computer Science 298 (2003) 207-233			bib
	J.C. Riquelme, J.S. Aguilar-Ruiz, M. Toro. Finding representative patterns with ordered projections. Pattern Recognition 36 (2003) 1009-1018			bib
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2002
	H. Brighton, C. Mellish. Advances in instance selection for instance-based learning algorithms. Data Mining and Knowledge Discovery 6 (2002) 153-172			bib
	V.S. Devi, M.N. Murty. An incremental prototype set building technique. Pattern Recognition 35:2 (2002) 505-513			bib
	H. Liu, H. Motoda. On issues of instance selection. Data Mining and Knowledge Discovery 6 (2002) 115-130			bib
	R.A. Mollineda, F.J. Ferri, E. Vidal. An efficient prototype merging strategy for the condensed 1-NN rule through class-conditional hierarchical clustering. Pattern Recognition 35 (2002) 2771-2782			bib
	T. Reinartz. A unifying view on instance selection. Data Mining and Knowledge Discovery 6 (2002) 191-210			bib
	M. Sebban, R. Nock, S. Lallich. Stopping criterion for boosting-based data reduction techniques: from binary to multiclass problems. Journal of Machine Learning Research 3 (2002) 863-885			bib
	H. Zhang, G. Sun. Optimal reference subset selection for nearest neighbor classification by tabu search. Pattern Recognition 35 (2002) 1481-1490			bib
2001
	J.S. Aguilar-Ruiz, J.C. Riquelme, M. Toro. Data set editing by ordered projection. Intelligent Data Analysis 5:5 (2001) 405-417			bib
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2000
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	D.R. Wilson, T.R. Martinez. Reduction tecniques for instance-based learning algorithms. Machine Learning 38 (2000) 257-268			bib
	D.R. Wilson, T.R. Martinez. An integrated instance-based learning algorithm. Computational Intelligence 16:1 (2000) 1-28			bib
1999
	F.J. Ferri, J.V. Albert, E. Vidal. Considerations about sample-size sensitivity of a family of edited nearest-neighbor rules. IEEE Transactions on Systems, Man, and Cybernetics part B: Cybernetics 29:4 (1999) 667-672			bib
1997
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 Contributions to Books Chapters

Jump to Year:   2005  2001

2005
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2001
	H. Liu, H. Motoda. Data Reduction via Instance Selection. In: H. Liu, H. Motoda (Eds.) Instance Selection and Construction for Data Mining, Kluwer Academic Publishers, 2001, 3-20			bib

 Conference Contributions

Jump to Year:   2006  2005  2004  2003  2002  2001  2000

2006
	C.H. Chou, B.H. Kuo, F. Chang. The Generalized Condensed Nearest Neighbor Rule as a Data Reduction Method. 18th International Conference on Pattern Recognition (ICPR06). Hong Kong (China, 2006) 556-559			bib
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	S.H. Son, J.Y. Kim. Data reduction for instance-based learning using entropy-based partitioning. International Conference on Computational Science and its Applications (ICCSA06). Lecture Notes in Computer Science 3982, Springer-Verlag 2006, Glasgow (Scotland, 2006) 590-599			bib
	B. Spillmann, M. Neuhaus, H. Bunke, E. Pekalska, R.P.W. Duin. Transforming strings to vector spaces using prototype selection. Structural and Syntactic Pattern Recognition and Statistical Techniques in Pattern Recognition (SSPR-SPR06). Lecture Notes in Computer Science 4109, Springer-Verlag 2006, Hong Kong (China, 2006) 287-296			bib
	A. Srisawat, T. Phienthrakul, B. Kijsirikul. SV-kNNC: An algorithm for improving the efficiency of k-nearest neighbor. Pacific Rim International Conference on Artificial Intelligence (PRICAI06). Lecture Notes in Computer Science 4099, Springer-Verlag 2006, Guilin (China, 2006) 975-979			bib
	H. Zhao, B.L. Lu. A modular reduction method for k-NN algorithm with self-recombination learning. International Symposium on Neural Networks (ISNN06). Lecture Notes in Computer Science 3971, Springer-Verlag 2006, Chengdu (China, 2006) 537-544			bib
	X. Zhu, X. Wu. Scalable Representative Instance Selection and Ranking. 18th International Conference on Pattern Recognition (ICPR06). Hong Kong (China, 2006) 352-355			bib
2005
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2004
	M. Grochowski, N. Jankowski. Comparison of instance selection algorithms II. Algorithms survey. VII International Conference on Artificial Intelligence and Soft Computing (ICAISC'04). Lecture Notes in Computer Science 3070, Springer-Verlag 2004, Zakopane (Poland, 2004) 598-603			bib
	M. Grochowski, N. Jankowski. Comparison of instance selection algorithms II. Results and Comments. VII International Conference on Artificial Intelligence and Soft Computing (ICAISC'04). Lecture Notes in Computer Science 3070, Springer-Verlag 2004, Zakopane (Poland, 2004) 580-585			bib
	Y. Jiang, Z.H. Zhou. Editing training data for kNN classifiers with neural network ensemble. I International Symposium on Neural Networks (ISNN'04). Lecture Notes in Computer Science 3173, Springer-Verlag 2004, Dalian (China, 2004) 356-361			bib
	Z.H. Zhou, D. Wei, G. Li, H. Dai. On the size of training set and the benefit from ensemble. VIII Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'04). Lecture Notes in Computer Science 3056, Springer-Verlag 2004, Sydney (Australia, 2004) 298-307			bib
2003
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	K.P Zhao, S.G. Zhou, J.H. Guan, A.Y. Zhou. C-Pruner: An improved instance prunning algorithm. Second International Conference on Machine Learning and Cybernetics (ICMLC'03). Xian (China, 2003) 94-99			bib
2002
	D. Fragoudis, D. Meretakis, S. Likothanassis. Integrating feature and instance selection for text classification. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. (2002) 501-506			bib
2001
	K. Yu, X. Xu, M. Ester, H.P. Kriegel. Selecting relevant instances for efficient and accurate collaborative filtering. International Conference on Information and Knowledge Management (ICIKM01). (2001) 239-246			bib
2000
	J. Kangas. Comparison between Two Prototype Representation Schemes for Nearest Neighbor Classifier. 15th International Conference on Pattern Recognition (ICPR00). Barcelona (Spain, 2000) 773-776			bib

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