Mahesan Niranjan

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20EEYang Zhang, HongYu Li, Mahesan Niranjan, Peter Rockett: Applying Cost-Sensitive Multiobjective Genetic Programming to Feature Extraction for Spam E-mail Filtering. EuroGP 2008: 325-336
19EERenata da Silva Camargo, Mahesan Niranjan: Mining Protein Database using Machine Learning Techniques. J. Integrative Bioinformatics 5(2): (2008)
18EESujimarn Suwannaroj, Mahesan Niranjan: Enhancing Automatic Construction of Gene Subnetworks by Integrating Multiple Sources of Information. Signal Processing Systems 50(3): 331-340 (2008)
17 Joab Winkler, Mahesan Niranjan, Neil D. Lawrence: Deterministic and Statistical Methods in Machine Learning, First International Workshop, Sheffield, UK, September 7-10, 2004, Revised Lectures Springer 2005
16EENeil D. Lawrence, Marta Milo, Mahesan Niranjan, Penny Rashbass, Stephan Soullier: Reducing the variability in cDNA microarray image processing by Bayesian inference. Bioinformatics 20(4): (2004)
15EESi Wu, Danmei Chen, Mahesan Niranjan, Shun-ichi Amari: Sequential Bayesian Decoding with a Population of Neurons. Neural Computation 15(5): 993-1012 (2003)
14EEGaafar M. K. Saleh, Mahesan Niranjan: Speech enhancement using a Bayesian evidence approach. Computer Speech & Language 15(2): 101-125 (2001)
13 João F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee: Hierarchical Bayesian Models for Regularization in Sequential Learning. Neural Computation 12(4): 933-953 (2000)
12 João F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee, Arnaud Doucet: Sequential Monte Carlo Methods to Train Neural Network Models. Neural Computation 12(4): 955-993 (2000)
11EEJoão F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee: Dynamic Learning with the EM Algorithm for Neural Networks. VLSI Signal Processing 26(1-2): 119-131 (2000)
10EEGavin Smith, João F. G. de Freitas, Tony Robinson, Mahesan Niranjan: Speech Modelling Using Subspace and EM Techniques. NIPS 1999: 796-802
9EEMartin J. J. Scott, Mahesan Niranjan, Richard W. Prager: Realisable Classifiers: Improving Operating Performance on Variable Cost Problems. BMVC 1998
8EEJoão F. G. de Freitas, Mahesan Niranjan, Arnaud Doucet, Andrew H. Gee: Global Optimisation of Neural Network Models via Sequential Sampling. NIPS 1998: 410-416
7EED. R. Lovell, Christopher R. Dance, Mahesan Niranjan, Richard W. Prager, Kevin J. Dalton, R. Derom: Feature selection using expected attainable discrimination. Pattern Recognition Letters 19(5-6): 393-402 (1998)
6 João F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee: Regularisation in Sequential Learning Algorithms. NIPS 1997
5EESean B. Holden, Mahesan Niranjan: Average-Case Learning Curves for Radial Basis Function Networks. Neural Computation 9(2): 441-460 (1997)
4EEMahesan Niranjan: Sequential Tracking in Pricing Financial Options using Model Based and Neural Network Approaches. NIPS 1996: 960-966
3EESean B. Holden, Mahesan Niranjan: On the practical applicability of VC dimension bounds. Neural Computation 7(6): 1265-1288 (1995)
2 Mahesan Niranjan, Frank Fallside: Speech Feature Extraction Using Neural Networks. EURASIP Workshop 1990: 197-204
1EEVisakan Kadirkamanathan, Mahesan Niranjan, Frank Fallside: Sequential Adaptation of Radial Basis Function Networks. NIPS 1990: 721-727

Coauthor Index

1Shun-ichi Amari [15]
2Renata da Silva Camargo [19]
3Danmei Chen [15]
4Kevin J. Dalton [7]
5Christopher R. Dance [7]
6R. Derom [7]
7Arnaud Doucet [8] [12]
8Frank Fallside [1] [2]
9João F. G. de Freitas [6] [8] [10] [11] [12] [13]
10Andrew H. Gee [6] [8] [11] [12] [13]
11Sean B. Holden [3] [5]
12Visakan Kadirkamanathan [1]
13Neil D. Lawrence [16] [17]
14HongYu Li [20]
15D. R. Lovell [7]
16Marta Milo [16]
17Richard W. Prager [7] [9]
18Penny Rashbass [16]
19Tony Robinson [10]
20Peter Rockett [20]
21Gaafar M. K. Saleh [14]
22Martin J. J. Scott [9]
23Gavin Smith [10]
24Stephan Soullier [16]
25Sujimarn Suwannaroj [18]
26Joab Winkler [17]
27Si Wu [15]
28Yang Zhang [20]

Colors in the list of coauthors

Copyright © Sun May 17 03:24:02 2009 by Michael Ley (ley@uni-trier.de)