Operations Research/Computer Science Interfaces

Preface. Part I: Invited Papers. 1. N-Tuple Neural Networks; N.M. Allinson, A.R. Kolcz. 2. Information Geometry of Neural Networks - An Overview; S. Amari. 3. Q-Learning: A Tutorial and Extensions; G. Cybenko, et al. 4. Are There Universal Principles of Brain Computation? S. Grossberg. 5. On-Line Training of Memory-Driven Attractor Networks; M.W. Hirsch. 6. Mathematical Problems Arising from Constructing An Artificial Brain; J.G. Taylor. Part II: Submitted Papers. 7. The Successful Use of Probability Data in Connectionist Models; J.R. Alexander Jr., J.P. Coughlin. 8. Weighted Mixture of Models for On-Line Learning; P.E. An. 9. Local Modifications to Radial Basis Networks; I.J. Anderson. 10. A Statistical Analysis of the Modified NLMS Rules; E.D. Aved'yan, et al. 11. Finite Size Effects in On-Line Learning of Multi-Layer Neural Networks; D. Barber, et al. 12. Constant Fan-in Digital Neural Networks Are VLSI-Optimal; V. Beiu. 13. The Application of Binary Encoded 2nd Differential Spectrometry in Preprocessing of UV-VIS Absorption Spectral Data; N. Benjathapanun, et al. 14. A Non-Equidistant Elastic Net Algorithm; J. van den Berg, J.H. Geselschap. 15. Unimodal Loading Problems; M. Bianchini, et al. 16. On the Use of Simple Classifiers for the Initialisation of One-Hidden-Layer Neural Nets; J.C. Bioch, et al. 17. Modelling Conditional Probability Distributions for Periodic Variables; C.M. Bishop, I.T. Nabney. 18. Integro-Differential Equations in Compartmental Model Neurodynamics; P.C. Bressloff. 19. Nonlinear Models for Neural Networks; S. Brittain, L.M. Haines. 20. A Neural Network for the Travelling Salesman Problem with a Well Behaved Energy Function; M. Budinich, B. Rosario. 21. Semiparametric Artificial Neural Networks; E. Capobianco. 22. An Event-Space Feedforward Network Using Maximum Entropy Partitioning With Application to Low Level Speech Data; D.K.Y. Chiu, et al. 23. Approximating the Bayesian Decision Boundary for Channel Equalisation Using Subset Radial Basis Function Network; E.S. Chng, et al. 24. Applications of Graph Theory to the Design of Neural Networks for Automated Fingerprint Identification; C.G. Crawford. 25. Zero Dynamics and Relative Degree of Dynamic Recurrent Neural Networks; A. Delgado, et al. 26. Irregular Sampling Approach to Neurocontrol: The Band-and Space-Limited Functions Questions; A. Dzielinski, R. Zbikowski. 27. Unsupervised Learning of Temporal Constancies by Pyramidal-Type Neurons; M. Eisele. 28. Numerical Aspects of Machine Learning in Artificial Neural Networks; S.W. Ellacott, A. Easdown. 29. Learning Algorithms for RAM-Based Neural Networks; A. Ferguson, et al. 30. Analysis of Correlation Matrix Memory and Partial Match-Implications for Cognitive Psychology; R. Filer, J. Austin. 31. Regularization and Realizability in Radial Basis Function Networks; J.A.S. Freeman, D. Saad. 32. A Universal Approximator Network for Learning Conditional Probability Densities; D. Husmeier, et al. 33. Convergence of a Class of Neural Networks; M.P. Joy. 34. Applications of the Compartmental Model Neuron to Time Series Analysis; S. Kasderidis, J.G. Taylor. 35. Information Theoretic Neural Networks for Contextually Guided Unsupervised Learning; J. Kay. 36. Convergence in Noisy Training; P. Koistinen. 37. Non-Linear Learning Dynamics with a Diffusing Messenger; B. Krekelberg, J.G. Taylor. 38. A Variational Approach to Associative Memory; A. Labbi. 39. Transformation of Nonlinear Programming Problems into Separable Ones Using Multilayer Neural Networks; Bao- Liang Lu, K. Ito. 40. A Theory of Self-Organising Neural Networks; S.P. Luttrell. 41. Neural Network Supervised Training Based on a Dimension Reducing Method; G.D. Magoulas, et al. 42. A Training Method for Discrete Multilayer Neural Networks; G.D. Magoulas, et al. 43. Local Minimal Realisations of Trained Hopfield Networks; S. Manchanda, G.G.R. Green. 44. Data Dependent Hyperparameter Assignment; G. Marion, D. Saad. 45. Training Radial Basis Function Networks by Using Separable and Orthogonalized Gaussians; J.C. Mason, et al. 46. Error Bounds for Density Estimation by Mixtures; R. Meir, A.J. Zeevi. 47. On Smooth Activation Functions; H.N. Mhaskar. 48. Generalisation and Regularisation by Gaussian Filter Convolution of Radial Basis Function Networks; C. Molina, M. Niranjan. 49. Dynamical System Prediction: A Lie Algebraic Approach for a Novel Neural Architecture; Y. Moreau, J. Vandewalle. 50. Stochastic Neurodynamics and the System Size Expansion; T. Ohira, J.D. Cowan. 51. An Upper Bound on the Bayesian Error Bars for Generalized Linear Regression; C.S. Qazaz, et al. 52. Capacity Bounds for Structured Neural Network Architectures; P. Rieper, et al. 53. On-Line Learning in Multilayer Neural Networks; D. Saad, S.A. Solla. 54. Spontaneous Dynamics and Associative Learning in an Asymmetric Recurrent Random Neural Network; M. Samuelides, et al. 55. A Statistical Mechanics Analysis of Genetic Algorithms for Search and Learning; J.L. Shapiro, et al. 56. Volumes of Attraction Basins in Randomly Connected Boolean Networks; S.A. Shumsky. 57. Evidential Rejection Strategy for Neural Network Classifiers; A. Shustorovich. 58. Dynamics Approximation and Change Point Retrieval from a Neural Network Model; J. Smid, P. Volf. 59. Query Learning for Maximum Information Gain in a Multi-Layer Neural Network; P. Sollich. 60. Shift, Rotation and Scale Invariant Signatures for Two-Dimensional Contours, in a Neural Network Architecture; D. McG. Squire, T.M. Caelli. 61. Function Approximation by Three-Layer Artificial Neural Networks; S. Suzuki. 62. Neural Network Versus Statistical Clustering Techniques: A Pilot Study in a Phoneme Recognition Task; G. Tambouratzis, et al. 63. Multispectral Image Analysis Using Pulsed Coupled Neural Networks; G.L. Tarr, et al. 64. Reasoning Neural Networks; Rua-Huan R. Tsaih. 65. Capacity of the Upstart Algorithm; A.H.L. West, D. Saad. 66. Regression with Gaussian Processes; C.K.I, Williams. 67. Stochastic Forward-Perturbation, Error Surface and Progressive Learning in Neural Networks; Li-Qun Xu. 68. Dynamical Stability of a High-Dimensional Self-Organizing Map; Howard Hua Yang. 69. Measurements of Generalisation Based on Information Geometry; Huaiyu Zhu, R. Rohwer. 70. Towards an Algebraic Theory of Neural Networks: Sequential Composition; R. Zimmer.