Next: About this document Up: Similarity Metric Learning for Previous: Conclusions and future

References

Atkeson, C.G. 1989. Learning arm kinematics and dynamics. Annual Review of Neuroscience 12, 157--83.

Atkeson, C.G. 1991. Using locally weighted regression for robot learning. IEEE Conf. on Robotics and Automation, Sacramento, CA, 958--963.

Bottou, L., and Vapnik, V. 1992. Local learning algorithms. Neural Computation, 4, 888--900.

Broomhead, D.S., and Lowe, D. 1988. Multivariable functional interpolation and adaptive networks. Complex Systems, 2, 321--355.

Chang, C.L. 1974. Finding prototypes for nearest neighbour classifiers. IEEE Transactions on Computers, 23, 1179--84.

Cleveland, W.S., and Devlin, S.J. 1988. Locally weighted regression: An approach to regression analysis by local fitting. Journal of the American Statistical Association, 83, 596--610.

Cover, T.M., and Hart, P.E. 1967. Nearest neighbour pattern classification. IEEE Transactions on Information Theory, IT-13, 1, 21--27.

Dasarathy, B.V. 1991. NN concepts and techniques. Nearest Neighbour (NN) Norms: NN Pattern Classification Techniques, B.V. Dasarathy (Ed.), IEEE Computer Society Press, 1--30.

Duda, R.O. and Hart, P.E. 1973. Pattern Classification and Scene Analysis. New York: Wiley.

Friedman, J.H., Bentley, J.L., and Finkel, R.A. 1977. An algorithm for finding best matches in logarithmic expected time. ACM Trans. Math. Software, 3, 209--226.

Gorman, R.P. and Sejnowski, T.J. 1988. Analysis of hidden units in a layered network trained to classify sonar targets. Neural Networks, 1, 75--89.

Moody, J., and Darken, C.J. 1989. Fast learning in networks of locally-tuned processing units. Neural Computation, 1, 281--294.

Omohundro, S.M. 1992. Best-first model merging for dynamic learning and recognition, Advances in Neural Information Processing Systems 4, Morgan Kaufmann, Denver, 958--965.

Poggio, T., and Girosi, F. 1989. A theory of networks for approximation and learning. Report AI-1140, MIT Artificial Intelligence Laboratory, Cambridge, MA.

Poggio, T., and Girosi, F. 1990. Extensions of a theory of networks for approximation and learning: dimensionality reduction and clustering. Report AI-1167, MIT Artificial Intelligence Laboratory, Cambridge, MA.

Robinson, A.J. 1989. Dynamic error propagation networks, Ph.D. thesis, Cambridge University Engineering Department.

Sejnowski, T.J., and Rosenberg, C.R. 1987. Parallel networks that learn to pronounce English text. Complex Systems, 1, 145--168.

Silverman, B.W. 1986. Density Estimation for Statistics and Data Analysis, Chapman and Hall, London.

Sproull, R.F. 1991. Refinements to nearest-neighbour searching in k-d trees. Algorithmica, 6, 579--589.

Stanfill, C., and Waltz, D. 1986. Toward memory-based reasoning. Communications of the ACM, 29, 1213--1228.

Tomek, I. 1976. An experiment with the edited nearest-neighbour rule. IEEE Transactions on Systems, Man and Cybernetics, 6, 448--452.

Wettschereck, D., and Dietterich, T. 1992. Improving the performance of radial basis function networks by learning center locations, Advances in Neural Information Processing Systems 4, Morgan Kaufmann, Denver, 1133--40.

Wolpert, D.H. 1990. Constructing a generalizer superior to NETtalk via a mathematical theory of generalization. Neural Networks, 3, 445--452.




Next: About this document Up: Similarity Metric Learning for Previous: Conclusions and future



David Lowe
Wed Jul 16 17:08:22 PDT 1997