Publications

Dissertation:

  • Michael Rimer, Improving Neural Network Classification Training, Ph.D. dissertation, Brigham Young University, 2007.

    Masters thesis:

  • Michael Rimer, Lazy Training: Interactive Classification Learning, Masters Thesis, Brigham Young University, 2002.

    Journal publications:

  • Rimer, M. & Martinez, T., Classification-based Objective Functions, Machine Learning, vol. 63, no. 2, pp. 183-205, 2006.

  • Rimer, M. & Martinez, T., CB3: An Adaptive Error Function for Backpropagation Training, Neural Processing Letters, vol. 24, no. 1, pp. 81-92, 2006.

    Conference publications:

  • Rimer, M., Andersen, T. and Martinez, T.R., Improving Backpropagation Ensembles through Lazy Training, Proceedings of the IEEE International Joint Conference on Neural Networks IJCNN'01, pp. 2007-2112, 2001.

  • Rimer, M., Andersen, T. and Martinez, T.R., Speed Training: Improving Learning Speed for Large Data Sets, Proceedings of the IEEE International Joint Conference on Neural Networks IJCNN'01, pp. 2662-2666, 2001.

  • Andersen, T., Rimer, M. and Martinez, T.R., Optimal Artificial Neural Network Architecture Selection for Voting, Proceedings of the IEEE International Joint Conference on Neural Networks IJCNN'01, pp. 790-795, 2001.

  • Rimer, M., Martinez, T.R. & Wilson, D., Improving Speech Recognition Learning through Lazy Training, Proceedings of the IEEE International Joint Conference on Neural Networks IJCNN'02, pp. 2568-2573, 2002.

  • J. Menke, A. Peterson, M. Rimer, T.R. Martinez, Network Simplification Through Oracle Learning, Proceedings of the IEEE International Joint Conference on Neural Networks IJCNN'02, pp. 2482-2497, 2002.

  • Rimer, M. & Martinez, T., Softprop: Softmax Neural Network Backpropagation Learning, Proceedings of the IEEE International Joint Conference on Neural Networks IJCNN'04, pp. , 2004.

    Other works:

  • Michael Rimer, Higher order feature detection through the combination of minimalized subnets, Brigham Young University, 1999.

  • Michael Rimer, Properties of lookahead decision trees, Brigham Young University, 2000.

    • See some quotes on research and inspiration.

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    Last modified 1 Sep 2007

    (mrimer at cs dot byu dot edu)