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Volumn 8, Issue 2, 2009, Pages 125-149

Representation in the (artificial) immune system

Author keywords

Artificial immune system; Learning; Representation; Shape space

Indexed keywords


EID: 67349200268     PISSN: 15701166     EISSN: 15729214     Source Type: Journal    
DOI: 10.1007/s10852-009-9104-6     Document Type: Conference Paper
Times cited : (13)

References (58)
  • 1
    • 84949479246 scopus 로고    scopus 로고
    • On the Surprising Behavior of Distance Metrics in High Dimensional Spaces
    • C.C. Aggarwal A. Hinneburg D.A. Keim 2001 On the surprising behavior of distance metrics in high dimensional space Lect. Notes Comput. Sci. 1973 420 434 (Pubitemid 33213340)
    • (2001) LECTURE NOTES in COMPUTER SCIENCE , Issue.1973 , pp. 420-434
    • Aggarwal, C.C.1    Hinneburg, A.2    Keim, D.A.3
  • 2
    • 33750383209 scopus 로고    scopus 로고
    • K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation
    • DOI 10.1109/TSP.2006.881199
    • M. Aharon M. Elad A. Bruckstein 2006 K-svd: an algorithm for designing overcomplete dictionaries for sparse representation IEEE Trans. Signal Process. 54 4311 4322 (Pubitemid 44637761)
    • (2006) IEEE Transactions on Signal Processing , vol.54 , Issue.11 , pp. 4311-4322
    • Aharon, M.1    Elad, M.2    Bruckstein, A.3
  • 9
    • 0000275022 scopus 로고    scopus 로고
    • Prediction games and arcing algorithms
    • L. Breiman 1999 Prediction games and arcing algorithms Neural Comput. 11 7 1493 1517
    • (1999) Neural Comput. , vol.11 , Issue.7 , pp. 1493-1517
    • Breiman, L.1
  • 11
    • 0030597113 scopus 로고    scopus 로고
    • A model of the immune network with B-T cell co-operation. I-Prototypical structures and dynamics
    • DOI 10.1006/jtbi.1996.0192
    • J. Carneiro A. Coutinho J. Faro J. Stewart 1996 A model of the immune network with b-t cell co-operation. i-prototypicalstructures and dynamics J. Theor. Biol. 182 513 529 (Pubitemid 26375701)
    • (1996) Journal of Theoretical Biology , vol.182 , Issue.4 , pp. 513-529
    • Carneiro, J.1    Coutinho, A.2    Faro, J.3    Stewart, J.4
  • 12
    • 0030597105 scopus 로고    scopus 로고
    • A model of the immune network with B-T cell co-operation. II - The simulation of ontogenesis
    • DOI 10.1006/jtbi.1996.0193
    • J. Carneiro A. Coutinho J. Stewart 1996 A model of the immune network with b-t cell co-operation. ii-the simulation of ontogenisis J. Theor. Biol. 182 531 547 (Pubitemid 26375702)
    • (1996) Journal of Theoretical Biology , vol.182 , Issue.4 , pp. 531-547
    • Carneiro, J.1    Coutinho, A.2    Stewart, J.3
  • 13
    • 0028168537 scopus 로고
    • Rethinking ″shape space″: Evidence from simulated docking suggests that steric shape complementarity is not limiting for antibody-antigen recognition and idiotypic interactions
    • DOI 10.1006/jtbi.1994.1161
    • J. Carneiro J. Stewart 1994 Rethinking shape space: evidence from simulated docking suggeststhat steric shape complementarity is not limiting for antibody-antigenrecognition and idiotypic interactions J. Theor. Biol. 169 391 402 (Pubitemid 2124588)
    • (1994) Journal of Theoretical Biology , vol.169 , Issue.4 , pp. 391-402
    • Carneiro, J.1    Stewart, J.2
  • 14
    • 33750379819 scopus 로고    scopus 로고
    • Immune system computation and the immunological homunculus
    • Niestrasz, O., et al. (ed.) Genova, 1-6 October
    • Cohen, I.R.: Immune system computation and the immunological homunculus. In: Niestrasz, O., et al. (ed.) MoDELS 2006, pp. 499-512, Genova, 1-6 October 2006
    • (2006) MoDELS 2006 , pp. 499-512
    • Cohen, I.R.1
  • 22
    • 46149127936 scopus 로고
    • The immune system, adaptation and machine learning
    • J.D. Farmer N.H. Packard A.S. Perelson 1986 The immune system, adaptation and machine learning Physica 22 187 204
    • (1986) Physica , vol.22 , pp. 187-204
    • Farmer, J.D.1    Packard, N.H.2    Perelson, A.S.3
  • 24
    • 34547858478 scopus 로고    scopus 로고
    • Revisiting the foundations of artificial immune systems for data mining
    • DOI 10.1109/TEVC.2006.884042
    • A.A. Freitas J. Timmis 2007 Revisiting the foundations of artificial immune systems for datamining IEEE Trans. Evol. Comput. 11-4 521 540 (Pubitemid 47250406)
    • (2007) IEEE Transactions on Evolutionary Computation , vol.11 , Issue.4 , pp. 521-540
    • Freitas, A.A.1    Timmis, J.2
  • 26
    • 0031211090 scopus 로고    scopus 로고
    • A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting
    • Y. Freund R.E. Schapire 1997 A decision theoretic generalisation of on-line learning and an applicationto boosting J. Comput. Syst. Sci. 55 1 119 139 (Pubitemid 127433398)
    • (1997) Journal of Computer and System Sciences , vol.55 , Issue.1 , pp. 119-139
    • Freund, Y.1    Schapire, R.E.2
  • 27
    • 0003591748 scopus 로고    scopus 로고
    • Greedy function approximation: A gradient boosting machine
    • Friedman, J.: Greedy function approximation: a gradient boosting machine. IMS 1999 Reitz Lecture (1999)
    • (1999) IMS 1999 Reitz Lecture
    • Friedman, J.1
  • 28
    • 0034164230 scopus 로고    scopus 로고
    • ADDITIVE LOGISTIC REGRESSION: A STATISTICAL VIEW of BOOSTING
    • J. Friedman T. Hastie R. Tibshirani 2000 Additive logistic regression: a statistical view of boosting Ann. Stat. 28 337 407 (Pubitemid 33227445)
    • (2000) Annals of Statistics , vol.28 , pp. 337-407
    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
  • 29
    • 33845277062 scopus 로고    scopus 로고
    • Recent advances in predictive (machine) learning
    • Friedman, J.H.: Recent advances in predictive (machine) learning. In: PHYSTAT2003 (2003)
    • (2003) PHYSTAT2003
    • Friedman, J.H.1
  • 31
    • 26944451244 scopus 로고    scopus 로고
    • Application areas of ais: The past, the present and the future
    • ICARIS 2005
    • Hart, E., Timmis, J.: Application areas of ais: the past, the present and the future. In: ICARIS 2005, LNCS 3627 (2005)
    • (2005) LNCS , vol.3627
    • Hart, E.1    Timmis, J.2
  • 35
    • 34250890735 scopus 로고    scopus 로고
    • Real and artificial immune systems: Computing the state of the body
    • DOI 10.1038/nri2102, PII NRI2102
    • E.I.R. Cohen 2007 Real and artificial immune systems: computing the state of the body Nat. Rev. Immunol. 7 569 574 (Pubitemid 46987782)
    • (2007) Nature Reviews Immunology , vol.7 , Issue.7 , pp. 569-574
    • Cohen, I.R.1
  • 41
    • 0034133184 scopus 로고    scopus 로고
    • Learning overcomplete representations
    • M.S. Lewicki T.J. Sejnowski 2000 Learning overcomplete representations Neural Comput. 12 2 337 365
    • (2000) Neural Comput. , vol.12 , Issue.2 , pp. 337-365
    • Lewicki, M.S.1    Sejnowski, T.J.2
  • 43
    • 35148838877 scopus 로고
    • The weighted majority algorithm
    • N. Littlestone M.K. Warmuth 1994 The weighted majority algorithm Inf. Comput. 108 212 261
    • (1994) Inf. Comput. , vol.108 , pp. 212-261
    • Littlestone, N.1    Warmuth, M.K.2
  • 45
    • 0027842081 scopus 로고
    • Matching pursuits with time-frequency dictionaries
    • S.G. Mallat 1993 Matching pursuits with time-frequency dictionaries IEEE Trans. Signal Process. 41 3397 3415
    • (1993) IEEE Trans. Signal Process. , vol.41 , pp. 3397-3415
    • Mallat, S.G.1
  • 48
    • 35048849524 scopus 로고    scopus 로고
    • Nootropia: A user profiling model based on a self-organising termnetwork
    • ICARIS 2004
    • Nanas, N., Uren, V.S., de Roeck, A.: Nootropia: a user profiling model based on a self-organising termnetwork. In: ICARIS 2004, LNCS 3239 (2004)
    • (2004) LNCS , vol.3239
    • Nanas, N.1    Uren, V.S.2    De Roeck, A.3
  • 50
    • 0018567632 scopus 로고
    • Theoretical studies of clonal selection: Minimal antibody repertoire size and reliability of self-non-self discrimination
    • DOI 10.1016/0022-5193(79)90275-3
    • A.S. Perelson G. Oster 1979 Theoretical studies of clonal selection: minimal antibody repertoire size and reliability of self non-self discrimination J. Theor. Biol. 81 645 670 (Pubitemid 10178990)
    • (1979) Journal of Theoretical Biology , vol.81 , Issue.4 , pp. 645-670
    • Perelson, A.S.1    Oster, G.F.2
  • 52
    • 0025448521 scopus 로고
    • Strength of weak learnability
    • DOI 10.1023/A:1022648800760
    • R.E. Schapire 1990 The strength of weak learnability Mach. Learn. 5 197 227 (Pubitemid 20721695)
    • (1990) Machine Learning , vol.5 , Issue.2 , pp. 197-227
    • Schapire Robert, E.1
  • 54
    • 0036080160 scopus 로고    scopus 로고
    • Bagging, boosting and the random subspace method for linear classifiers
    • DOI 10.1007/s100440200011
    • M. Skurichina R.P.W. Duin 2002 Bagging, boosting and the random subspace method for linear classifiers Pattern Anal. Appl. 5 121 135 (Pubitemid 40830126)
    • (2002) Pattern Analysis and Applications , vol.5 , Issue.2 , pp. 121-135
    • Skurichina, M.1    Duin, R.P.W.2
  • 55
    • 67349220157 scopus 로고    scopus 로고
    • On the use of hyperspheres in artificial immune systems as antibodyrecognition regions
    • Stibor, T., Timmis, J., Eckert, C.: On the use of hyperspheres in artificial immune systems as antibodyrecognition regions. In: ICARIS 2006 (2006)
    • (2006) ICARIS 2006
    • Stibor, T.1    Timmis, J.2    Eckert, C.3
  • 57
    • 0025911312 scopus 로고
    • Second generation immune networks
    • F.J. Varela A. Coutinho 1991 Second generation immune networks Immunol. Today 12 5 159 166
    • (1991) Immunol. Today , vol.12 , Issue.5 , pp. 159-166
    • Varela, F.J.1    Coutinho, A.2
  • 58
    • 0036643065 scopus 로고    scopus 로고
    • Kernel matching pursuit
    • DOI 10.1023/A:1013955821559
    • P. Vincent Y. Bengio 2001 Kernel matching pursuit Mach. Learn. 48 169 191 (Pubitemid 34247577)
    • (2002) Machine Learning , vol.48 , Issue.1-3 , pp. 165-187
    • Vincent, P.1    Bengio, Y.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.