 | 2011 |
| 9 |  | Subhasis Mukherjee,
John Yearwood,
Peter Vamplew,
Md. Shamsul Huda:
Reinforcement Learning Approach to AIBO Robot's Decision Making Process in Robosoccer's Goal Keeper Problem.
SNPD 2011: 24-30 |
| 8 |  | Subhasis Mukherjee,
Md. Shamsul Huda,
John Yearwood:
A Reinforcement Learning Approach with Spline-Fit Object Tracking for AIBO Robot's High Level Decision Making.
SNPD (Selected Papers) 2011: 169-183 |
| 2010 |
| 7 |  | Md. Shamsul Huda,
John Yearwood,
Ron Borland:
Cluster Based Rule Discovery Model for Enhancement of Government's Tobacco Control Strategy.
NSS 2010: 383-390 |
| 6 |  | Md. Shamsul Huda,
John Yearwood,
Andrew Stranieri:
Hybrid Wrapper-Filter Approaches for Input Feature Selection Using Maximum Relevance and Artificial Neural Network Input Gain Measurement Approximation (ANNIGMA).
NSS 2010: 442-449 |
| 5 |  | Md. Shamsul Huda,
John Yearwood,
Ron Borland:
Smokers' Characteristics and Cluster Based Quitting Rule Discovery Model for Enhancement of Government's Tobacco Control Systems.
PACIS 2010: 26 |
| 2009 |
| 4 |  | Md. Shamsul Huda,
John Yearwood,
Roberto Togneri:
A Constraint-Based Evolutionary Learning Approach to the Expectation Maximization for Optimal Estimation of the Hidden Markov Model for Speech Signal Modeling.
IEEE Transactions on Systems, Man, and Cybernetics, Part B 39(1): 182-197 (2009) |
| 3 |  | Md. Shamsul Huda,
John Yearwood,
Roberto Togneri:
A stochastic version of Expectation Maximization algorithm for better estimation of Hidden Markov Model.
Pattern Recognition Letters 30(14): 1301-1309 (2009) |
| 2007 |
| 2 |  | Md. Shamsul Huda,
John Yearwood,
Ranadhir Ghosh:
A Hybrid Algorithm for Estimation of the Parameters of Hidden Markov Model based Acoustic Modeling of Speech Signals using Constraint-Based Genetic Algorithm and Expectation Maximization.
ACIS-ICIS 2007: 438-443 |
| 2006 |
| 1 |  | Md. Shamsul Huda,
Ranadhir Ghosh,
John Yearwood:
A Variable Initialization Approach to the EM Algorithm for Better Estimation of the Parameters of Hidden Markov Model Based Acoustic Modeling of Speech Signals.
Industrial Conference on Data Mining 2006: 416-430 |