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Mahesan Niranjan: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. M. J. J. Scott, Mahesan Niranjan, Richard W. Prager
    Realisable Classifiers: Improving Operating Performance on Variable Cost Problems. [Citation Graph (0, 0)][DBLP]
    BMVC, 1998, pp:- [Conf]
  2. Mahesan Niranjan, Frank Fallside
    Speech Feature Extraction Using Neural Networks. [Citation Graph (0, 0)][DBLP]
    EURASIP Workshop, 1990, pp:197-204 [Conf]
  3. João F. G. de Freitas, Mahesan Niranjan, Arnaud Doucet, Andrew H. Gee
    Global Optimisation of Neural Network Models via Sequential Sampling. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:410-416 [Conf]
  4. João F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee
    Regularisation in Sequential Learning Algorithms. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  5. Visakan Kadirkamanathan, Mahesan Niranjan, Frank Fallside
    Sequential Adaptation of Radial Basis Function Networks. [Citation Graph (0, 0)][DBLP]
    NIPS, 1990, pp:721-727 [Conf]
  6. Mahesan Niranjan
    Sequential Tracking in Pricing Financial Options using Model Based and Neural Network Approaches. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:960-966 [Conf]
  7. Gavin Smith, João F. G. de Freitas, Tony Robinson, Mahesan Niranjan
    Speech Modelling Using Subspace and EM Techniques. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:796-802 [Conf]
  8. Neil D. Lawrence, Marta Milo, Mahesan Niranjan, Penny Rashbass, Stephan Soullier
    Reducing the variability in cDNA microarray image processing by Bayesian inference. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2004, v:20, n:4, pp:- [Journal]
  9. João F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee
    Hierarchical Bayesian Models for Regularization in Sequential Learning. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:4, pp:933-953 [Journal]
  10. João F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee, Arnaud Doucet
    Sequential Monte Carlo Methods to Train Neural Network Models. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:4, pp:955-993 [Journal]
  11. Sean B. Holden, Mahesan Niranjan
    On the practical applicability of VC dimension bounds. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1995, v:7, n:6, pp:1265-1288 [Journal]
  12. Sean B. Holden, Mahesan Niranjan
    Average-Case Learning Curves for Radial Basis Function Networks. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1997, v:9, n:2, pp:441-460 [Journal]
  13. Si Wu, Danmei Chen, Mahesan Niranjan, Shun-ichi Amari
    Sequential Bayesian Decoding with a Population of Neurons. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2003, v:15, n:5, pp:993-1012 [Journal]
  14. D. R. Lovell, Christopher R. Dance, Mahesan Niranjan, Richard W. Prager, Kevin J. Dalton, R. Derom
    Feature selection using expected attainable discrimination. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 1998, v:19, n:5-6, pp:393-402 [Journal]
  15. Gaafar M. K. Saleh, Mahesan Niranjan
    Speech enhancement using a Bayesian evidence approach. [Citation Graph (0, 0)][DBLP]
    Computer Speech & Language, 2001, v:15, n:2, pp:101-125 [Journal]

  16. Applying Cost-Sensitive Multiobjective Genetic Programming to Feature Extraction for Spam E-mail Filtering. [Citation Graph (, )][DBLP]

  17. Exploiting Long-Range Dependencies in Protein beta-Sheet Secondary Structure Prediction. [Citation Graph (, )][DBLP]

  18. Sequential Hierarchical Pattern Clustering. [Citation Graph (, )][DBLP]

  19. Cross-Platform Analysis with Binarized Gene Expression Data. [Citation Graph (, )][DBLP]

  20. Reducing the algorithmic variability in transcriptome-based inference. [Citation Graph (, )][DBLP]

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