메뉴 건너뛰기




Volumn 10, Issue 2, 1997, Pages 343-352

The new ERA in supervised learning

Author keywords

global optimisation; homotopy; local minima; range expansion

Indexed keywords

APPROXIMATION THEORY; ERRORS; FUNCTIONS; NEURAL NETWORKS; OPTIMIZATION; VECTORS;

EID: 0031105896     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0893-6080(96)00090-1     Document Type: Article
Times cited : (23)

References (25)
  • 1
    • 0008996236 scopus 로고
    • Globally optimal neural learning
    • Hillsdale, NJ: Lawrence Erlbaum Associates & INNS Press
    • Barhen, J., Fijany, A., & Toomarian, N. (1994). Globally optimal neural learning. In Proceedings of WCNN'94. Hillsdale, NJ: Lawrence Erlbaum Associates & INNS Press, pp. III-370-III-375.
    • (1994) Proceedings of WCNN'94
    • Barhen, J.1    Fijany, A.2    Toomarian, N.3
  • 2
    • 0001024110 scopus 로고
    • First- and second-order methods for learning: Between steepest descent and Newton's method
    • Battiti, R. (1992). First- and second-order methods for learning: between steepest descent and Newton's method. Neural Computation, 4, 141-166.
    • (1992) Neural Computation , vol.4 , pp. 141-166
    • Battiti, R.1
  • 4
    • 0000669473 scopus 로고
    • Approximation of Boolean functions by sigmoidal networks: Part I: XOR and other two-variable functions
    • Blum, E. K. (1989). Approximation of Boolean functions by sigmoidal networks: Part I: XOR and other two-variable functions. Neural Computation, 1, 532-540.
    • (1989) Neural Computation , vol.1 , pp. 532-540
    • Blum, E.K.1
  • 6
    • 0027575229 scopus 로고
    • Terminal repeller unconstrained subenergy tunnelling (TRUST) for fast global optimization
    • Cetin, B. C., Barhen, J., & Burdick, J. W. (1993). Terminal repeller unconstrained subenergy tunnelling (TRUST) for fast global optimization. Journal of Optimization Theory and Applications, 77, 97-126.
    • (1993) Journal of Optimization Theory and Applications , vol.77 , pp. 97-126
    • Cetin, B.C.1    Barhen, J.2    Burdick, J.W.3
  • 7
    • 0003160484 scopus 로고
    • Towards faster stochastic gradient search
    • San Mateo, CA: Morgan Kauf\fman
    • Darken, C., & Moody, J. M. (1991). Towards faster stochastic gradient search. In Advances in Neural Information Systems 4. San Mateo, CA: Morgan Kauf\fman, pp. 1009-1016.
    • (1991) Advances in Neural Information Systems , vol.4 , pp. 1009-1016
    • Darken, C.1    Moody, J.M.2
  • 10
    • 0342426778 scopus 로고
    • Avoiding local minima using a range expansion algorithm
    • Gorse, D., Shepherd, A., & Taylor, J.G. (1993). Avoiding local minima using a range expansion algorithm. Neural Network World, 5, 503-510.
    • (1993) Neural Network World , vol.5 , pp. 503-510
    • Gorse, D.1    Shepherd, A.2    Taylor, J.G.3
  • 11
    • 0002358293 scopus 로고
    • A classical algorithm for avoiding local minima
    • Hillsdale, NJ: Lawrence Erlbaum Associates & INNS Press
    • Gorse, D., Shepherd, A., & Taylor, J. G. (1994). A classical algorithm for avoiding local minima. In Proceedings of WCNN'94. Hillsdale, NJ: Lawrence Erlbaum Associates & INNS Press, pp. III-364-III-369.
    • (1994) Proceedings of WCNN'94
    • Gorse, D.1    Shepherd, A.2    Taylor, J.G.3
  • 14
    • 0010235342 scopus 로고
    • Comparison and evaluation of variants of the conjugate gradient method for efficient learning in feed-forward neural networks with backward error propagation
    • Kinsella, J. A. (1992). Comparison and evaluation of variants of the conjugate gradient method for efficient learning in feed-forward neural networks with backward error propagation. Network, 3, 27-35.
    • (1992) Network , vol.3 , pp. 27-35
    • Kinsella, J.A.1
  • 15
  • 17
    • 0000294383 scopus 로고
    • Complete solution of the local minima in the XOR problem
    • Lisboa, P. J. G., & Perantonis, S. J. (1991). Complete solution of the local minima in the XOR problem. Network, 2, 119-124.
    • (1991) Network , vol.2 , pp. 119-124
    • Lisboa, P.J.G.1    Perantonis, S.J.2
  • 20
    • 0002932077 scopus 로고
    • Backpropagation can give rise to spurious local minima even for networks with no hidden layers
    • Sontag, E.D., & Sussman, H.J. (1989). Backpropagation can give rise to spurious local minima even for networks with no hidden layers. Complex Systems, 3, 91-106.
    • (1989) Complex Systems , vol.3 , pp. 91-106
    • Sontag, E.D.1    Sussman, H.J.2
  • 21
    • 0025839203 scopus 로고
    • Back propagation separates where perceptrons do
    • Sontag, E.D., & Sussman, H.J. (1991). Back propagation separates where perceptrons do. Neural Networks, 4, 243-249.
    • (1991) Neural Networks , vol.4 , pp. 243-249
    • Sontag, E.D.1    Sussman, H.J.2
  • 22
    • 45949121309 scopus 로고
    • Fast simulated annealing
    • Szu, H., & Hartley, R. (1987). Fast simulated annealing. Physics Letters, 122, 157-162.
    • (1987) Physics Letters , vol.122 , pp. 157-162
    • Szu, H.1    Hartley, R.2
  • 23
    • 0342861394 scopus 로고
    • Neural network models: A physicist's primer
    • R. D. Kenway and G. S. Pawley (Eds.). Edinburgh: Scottish Universities Summer Schools in Physics
    • Wallace, D. J. (1987). Neural network models: a physicist's primer. In R. D. Kenway and G. S. Pawley (Eds.), Computational Physics (SUSSP 32). Edinburgh: Scottish Universities Summer Schools in Physics, pp. 168-211.
    • (1987) Computational Physics (SUSSP 32) , pp. 168-211
    • Wallace, D.J.1
  • 25
    • 0024737058 scopus 로고
    • Dynamic tunnelling algorithms for global optimization
    • Yao, Y. (1989). Dynamic tunnelling algorithms for global optimization. IEEE Transactions on Systems, Man and Cybernetics, 19, 1222-1230
    • (1989) IEEE Transactions on Systems, Man and Cybernetics , vol.19 , pp. 1222-1230
    • Yao, Y.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.