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Volumn 3, Issue 2, 2006, Pages 131-145

An improved gradient projection-based decomposition technique for support vector machines

Author keywords

Decomposition techniques; Gradient projection methods; Large scale problems; Quadratic programs; Support vector machines

Indexed keywords


EID: 33645025197     PISSN: 1619697X     EISSN: 16196988     Source Type: Journal    
DOI: 10.1007/s10287-005-0004-6     Document Type: Article
Times cited : (25)

References (34)
  • 1
    • 0001531895 scopus 로고
    • Two-point step size gradient methods
    • Barzilai J, Borwein JM (1988) Two-point step size gradient methods. IMA J Numer Anal 8(1):141-148
    • (1988) IMA J Numer Anal , vol.8 , Issue.1 , pp. 141-148
    • Barzilai, J.1    Borwein, J.M.2
  • 3
    • 0034345420 scopus 로고    scopus 로고
    • Nonmonotone spectral projected gradient methods on convex sets
    • Birgin EG, Martínez JM, Raydan M (2000) Nonmonotone spectral projected gradient methods on convex sets. SIAM J Optim 10(4):1196-1211
    • (2000) SIAM J Optim , vol.10 , Issue.4 , pp. 1196-1211
    • Birgin, E.G.1    Martínez, J.M.2    Raydan, M.3
  • 5
    • 0003710380 scopus 로고    scopus 로고
    • LIBSVM: A library for support vector machines
    • www.csie.ntu.edu.tw/~cjlin/libsvm
    • Chang CC, Lin CJ (2001), LIBSVM: A library for support vector machines. www.csie.ntu.edu.tw/~cjlin/libsvm
    • (2001)
    • Chang, C.C.1    Lin, C.J.2
  • 6
    • 0000913324 scopus 로고    scopus 로고
    • SVMTorch: Support vector machines for large-scale regression problems
    • Collobert R, Bengio S (2001) SVMTorch: Support vector machines for large-scale regression problems. J Mach Learn Res 1:143-160
    • (2001) J Mach Learn Res , vol.1 , pp. 143-160
    • Collobert, R.1    Bengio, S.2
  • 8
    • 33645018300 scopus 로고    scopus 로고
    • New algorithms for singly linearly constrained quadratic programs subject to lower and upper bounds
    • (To appear). Also published as research report NA/216, Department of Mathematics, University of Dundee, Dundee, UK
    • Dai YH, Fletcher R (2005a) New algorithms for singly linearly constrained quadratic programs subject to lower and upper bounds. Math Program (To appear). Also published as research report NA/216, Department of Mathematics, University of Dundee, Dundee, UK
    • (2005) Math Program
    • Dai, Y.H.1    Fletcher, R.2
  • 9
    • 15544385032 scopus 로고    scopus 로고
    • Projected Barzilai-Borwein methods for large-scale box-constrained quadratic programming
    • Dai YH, Fletcher R (2005b) Projected Barzilai-Borwein methods for large-scale box-constrained quadratic programming. Numer Math 100(1):21-47
    • (2005) Numer Math , vol.100 , Issue.1 , pp. 21-47
    • Dai, Y.H.1    Fletcher, R.2
  • 10
    • 0011768018 scopus 로고    scopus 로고
    • On the Barzilai-Borwein method
    • Research report NA 207, Department of Mathematics, University of Dundee, Dundee UK
    • Fletcher R (2001) On the Barzilai-Borwein method. Research report NA 207, Department of Mathematics, University of Dundee, Dundee UK
    • (2001)
    • Fletcher, R.1
  • 11
    • 0020826623 scopus 로고
    • A numerically stable dual method for solving strictly convex quadratic programs
    • Goldfarb D, Idnani A (1983) A numerically stable dual method for solving strictly convex quadratic programs. Math Program 27:1-33
    • (1983) Math Program , vol.27 , pp. 1-33
    • Goldfarb, D.1    Idnani, A.2
  • 12
    • 0022766519 scopus 로고
    • A nonmonotone line search technique for Newton's method
    • Grippo L, Lampariello F, Lucidi S (1986) A nonmonotone line search technique for Newton's method. SIAM J Numer Anal 23:707-716
    • (1986) SIAM J Numer Anal , vol.23 , pp. 707-716
    • Grippo, L.1    Lampariello, F.2    Lucidi, S.3
  • 13
    • 0036853835 scopus 로고    scopus 로고
    • Nonmonotone globalization techniques for the Barzilai-Borwein gradient method
    • Grippo L, Sciandrone M (2002) Nonmonotone globalization techniques for the Barzilai-Borwein gradient method. Comput Optim Appl 23:143-169
    • (2002) Comput Optim Appl , vol.23 , pp. 143-169
    • Grippo, L.1    Sciandrone, M.2
  • 14
    • 0036158552 scopus 로고    scopus 로고
    • A simple decomposition method for support vector machines
    • Hsu CW, Lin CJ (2002) A simple decomposition method for support vector machines. Mach Learn 46:291-314
    • (2002) Mach Learn , vol.46 , pp. 291-314
    • Hsu, C.W.1    Lin, C.J.2
  • 15
    • 0002714543 scopus 로고    scopus 로고
    • Making large-scale SVM learning practical
    • Schölkopf B, Burges C, Smola A (eds). MIT, Cambridge
    • Joachims T (1998). Making large-scale SVM learning practical. Schölkopf B, Burges C, Smola A (eds). Advances in kernel methods - support vector learning. MIT, Cambridge
    • (1998) Advances in Kernel Methods - Support Vector Learning
    • Joachims, T.1
  • 16
    • 0036163654 scopus 로고    scopus 로고
    • Convergence of a generalized SMO algorithm for SVM classifier design
    • Keerthi S, Gilbert E (2002) Convergence of a generalized SMO algorithm for SVM classifier design. Mach Learn 46:351-360
    • (2002) Mach Learn , vol.46 , pp. 351-360
    • Keerthi, S.1    Gilbert, E.2
  • 17
    • 0000545946 scopus 로고    scopus 로고
    • Improvements to platt's SMO algorithm for SVM classifier design
    • Keerthi S, Shevade S, Bhattacharyya C, Murthy K (2001) Improvements to platt's SMO algorithm for SVM classifier design. Neural Comput 13:637-649
    • (2001) Neural Comput , vol.13 , pp. 637-649
    • Keerthi, S.1    Shevade, S.2    Bhattacharyya, C.3    Murthy, K.4
  • 18
    • 6344235947 scopus 로고    scopus 로고
    • The MNIST database of handwritten digits
    • yann.lecun.com/exdb/mnist
    • LeCun Y (1998) The MNIST database of handwritten digits yann.lecun.com/ exdb/mnist
    • (1998)
    • LeCun, Y.1
  • 19
    • 0035506741 scopus 로고    scopus 로고
    • On the convergence of the decomposition method for support vector machines
    • Lin CJ (2001a) On the convergence of the decomposition method for support vector machines. IEEE Trans Neural Netw 12:1288-1298
    • (2001) IEEE Trans Neural Netw , vol.12 , pp. 1288-1298
    • Lin, C.J.1
  • 20
  • 21
    • 0036129250 scopus 로고    scopus 로고
    • Asymptotic convergence of an SMO algorithm without any assumptions
    • Lin CJ (2002) Asymptotic convergence of an SMO algorithm without any assumptions. IEEE Trans Neural Netw 13:248-250
    • (2002) IEEE Trans Neural Netw , vol.13 , pp. 248-250
    • Lin, C.J.1
  • 22
    • 0003408496 scopus 로고
    • UCI repository of machine learning data-bases
    • www.ics.uci.edu/~mlearn/MLRepository.html
    • Murphy P, Aha D (1992) UCI repository of machine learning data-bases. www.ics.uci.edu/~mlearn/MLRepository.html
    • (1992)
    • Murphy, P.1    Aha, D.2
  • 25
    • 0000859664 scopus 로고
    • An algorithm for a singly constrained class of quadratic programs subject to upper and lower bounds
    • Pardalos PM, Kovoor N (1990) An algorithm for a singly constrained class of quadratic programs subject to upper and lower bounds. Math Program 46:321-328
    • (1990) Math Program , vol.46 , pp. 321-328
    • Pardalos, P.M.1    Kovoor, N.2
  • 26
    • 0003120218 scopus 로고    scopus 로고
    • Fast training of support vector machines using sequential minimal optimization
    • Schölkopf B, Burges C, Smola A (eds). MIT, Cambridge, MA
    • Platt JC (1998). Fast training of support vector machines using sequential minimal optimization. In: Schölkopf B, Burges C, Smola A (eds). Advances in kernel methods - support vector learning. MIT, Cambridge, MA
    • (1998) Advances in Kernel Methods - Support Vector Learning
    • Platt, J.C.1
  • 27
    • 84898983292 scopus 로고    scopus 로고
    • Using analytic QP and sparseness to speed training of support vector machines
    • Kearns M et al. (eds). MIT, Cambridge, MA
    • Platt JC (1999). Using analytic QP and sparseness to speed training of support vector machines. In: Kearns M et al. (eds). Advances in neural information processing systems, vol 11. MIT, Cambridge, MA
    • (1999) Advances in Neural Information Processing Systems , vol.11
    • Platt, J.C.1
  • 28
    • 0034134885 scopus 로고    scopus 로고
    • A modified projection algorithm for large strictly convex quadratic programs
    • Ruggiero V, Zanni L (2000a) A modified projection algorithm for large strictly convex quadratic programs. J Optim Theory Appl 104(2):281-299
    • (2000) J Optim Theory Appl , vol.104 , Issue.2 , pp. 281-299
    • Ruggiero, V.1    Zanni, L.2
  • 31
    • 12444278992 scopus 로고    scopus 로고
    • Gradient projection methods for quadratic programs and applications in training support vector machines
    • Serafini T, Zanghirati G, Zanni L (2005) Gradient projection methods for quadratic programs and applications in training support vector machines. Optim Methods Softw 20:353-378
    • (2005) Optim Methods Softw , vol.20 , pp. 353-378
    • Serafini, T.1    Zanghirati, G.2    Zanni, L.3
  • 32
    • 27744479938 scopus 로고    scopus 로고
    • On the working set selection in gradient projection-based decomposition techniques for support vector machines
    • Serafini T, Zanni L (2005) On the working set selection in gradient projection-based decomposition techniques for support vector machines. Optim Methods Softw 20:583-596
    • (2005) Optim Methods Softw , vol.20 , pp. 583-596
    • Serafini, T.1    Zanni, L.2
  • 34
    • 0037378238 scopus 로고    scopus 로고
    • A parallel solver for large quadratic programs in training support vector machines
    • Zanghirati G, Zanni L (2003) A parallel solver for large quadratic programs in training support vector machines. Parallel Comput 29:535-551
    • (2003) Parallel Comput , vol.29 , pp. 535-551
    • Zanghirati, G.1    Zanni, L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.