Exploiting computer resources for fast nearest neighbor classification

Pattern Analysis and Applications

Volumn 10, Issue 4, 2007, Pages 265-275

  Herrero, José R ^a   Navarro, Juan J ^a  

^a UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 35248843586     PISSN: 14337541     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10044-007-0065-y     Document Type: Article

References (34)

1. Michie D, Spiegelhalter DJ, Taylor CC (1994) (eds) Machine learning, neural and statistical classification. Ellis Horwood, Chichester
2. Shakhnarovich G, Indyk P, Darrell T (2006) (eds) Nearest neighbor methods in learning and vision. Theory and practice. MIT Press, New York
3. Kevin B, Jonathan G, Raghu R, Uri S (1999) When is "nearest neighbour" meaningful? In: Catriel Beeri, Peter Buneman (eds) In: Proceedings of 7th international conference data theory, ICDT, number 1540 in lecture notes in computer science, LNCS. Springer, Heidelberg, 10-12 January 1999, pp 217-235
4. Mahamud S, Hebert M (2003) Minimum risk distance measure for object recognition. In: International conference on computer vision, pp 242-248
5. Pekalska E, Duin RPW, Gunter S, Bunke H (2004) On not making dissimilarities euclidean. In: Joint IAPR international workshops on statistical and structural pattern recognition, pp 1143-1151.
6. Vassilis Athitsos, Jonathan Alon, Stan Sclaroff (2005) Efficient nearest neighbor classification using a cascade of approximate similarity measures. In: IEEE computer vision and pattern recognition (CVPR), IEEE Computer Society, pp I: 486-493.
7. Kilian Q. Weinberger, John Blitzer, Lawrence K. Saul (2005) Distance metric learning for large margin nearest neighbor classification. In: Neural information processing systems, (NIPS)
8. Navarro JJ, Juan A, Lang T (1994) MOB forms: a class of multilevel block algorithms for dense linear algebra computations. In: ACM International conference supercomputing, pp. 354-363
9. Fu J, Huang TS (1984) VLSI for pattern recognition and image processing. Springer, Berlin
10. Bandyopadhyay S, Maulik U (2002) Efficient prototype reordering in nearest neighbor classification. Patt Recognit 35(12):2791-2799
11. Dasarathy BV (1991) Nearest Neighbor (NN) norms: NN pattern classification techniques, IEEE Computer Society Press, Washington
12. Grother PJ, Candela GT, Blue JL (1997) Fast implementation of nearest neighbor classifiers. Patt Recognit 30(3):459-465
13. Van Der Heiden R, Groen FCA (1997) The box-cox metric for nearest neighbor classification improvement. Patt Recognit 30(2):273-279
14. Kudo M, Masuyamaa N, Toyamaa J, Shimbob M (2003) Simple termination conditions for k-nearest neighbor method. Patt Recognit Lett 24(9-10):1203-1213
15. Lee EW, Chae SI (1998) Fast design of reduced-complexity nearest-neighbor classifiers using triangular inequality. IEEE Trans Patt Anal Mach Intell 20(5):562-566
16. Cheng-Lin Liu, Sako H, Fujisawa H (2002) Performance evaluation of pattern classifiers for handwritten character recognition. Int J Doc Anal Recog 4:191-204
17. Ricci F, Avesani P (1999) Data compression and local metrics for nearest neighbor classification. IEEE Trans Patt Anal Mach Intell 21(4):380-384
18. Djouadi A, Bouktache E (1997) A fast algorithm for the nearest-neighbor classifier. IEEE Trans Patt Anal Mach Intell 19(3):277-282
19. Harnamoto Y, Uchimura S, Tornita S (1997) A bootstrap technique for nearest neighbor classifier design. IEEE Trans Patt Anal Mach Intell 19(1):73-79
20. Pekalska E, Harol A, Lai C, Duin RPW (2005) Pairwise selection of features and prototypes. In: International conference on computer recognition systems, Springer, Heidelberg, pp 271-278
21. Decaestecker C (1997) Finding prototypes for nearest neighbor classification by means of gradient descent and deterministic annealing. Patt Recognit 30(2):281-288
22. Chi Z, Wu J, Yan H (1995) Handwritten numeral recognition using self-organizing maps and fuzzy rules. Patt Recognit 28(1):59-66
23. Kohonen T (1990) The self-organizing map. Proc IEEE 78(9):1464-1480
24. Baglietto P, Maresca M, Migliardi M (1996) Image processing on high-performance risc systems. In: Proc IEEE, 84(7):917-930
25. Anderson E, Dongarra J (1992) LAPACK user's guide. SIAM, Philadelphia
26. Hewlett Packard (1994) PA-RISC 1.1 Architecture and instruction set reference manual
27. Digital Equip. Corp. (1994) DECchip 21064 and DECchip 21064A Alpha AXP microprocessors-hardware ref. manual
28. SUN Microsystems (2003) UltraSPARC IIIi processor user's manual, June
29. Grother PJ, Candela GT (1993) Comparison of handprinted digit classifiers. Technical report NISTR 5209, National Institute of Standards and Technology (NIST)
30. Lam M (1999) Software pipelining: an effective technique for VLIW machines. In: Proceedings of the SIGPLAN'88, pp 318-3281999
31. John LH, David AP (1996) Computer architecture a quantitative approach, 2nd edn. Morgan Kaufmann, San Francisco
32. Lam MS, Rothberg EE, Wolf ME (1991) The cache performance and optimizations of blocked algorithms. In: Proceedings of ASPLOS'91, pp 67-74
33. Newman DJ, Hettich S, Blake CL, Merz CJ (1998) UCI repository of machine learning databases
34. Chih-Chung C, Chih-Jen L (2001) LIBSVM: a library for support vector machines. Available at http://www.csie.ntu.edu.tw/cjlin/libsvm