Problem Solver
Byron Shock
Areas Byron Shock is Knowledgeable in:
I am particularly knowledgeable and interested in machine learning, neural networks, and statistical pattern recognition. I have domain expertise in geographic information systems (GIS) and pattern classification for remote sensing problems. I am an expert in Matlab, Octave, S-Plus, and R technical programming as well as technical applications of logic and functional programming in Prolog and Erlang. I am conversant in Pascal, C++, and Visual Basic.
Techniques Byron Shock Uses:
I design machine learning methods that draw from the best available statistical, neural-network, and artificial intelligence research. I utilize statistically sound testing methodologies to compare multiple machine learning methods on a particular problem domain and select methods that are most appropriate for that domain.
Byron Shock's Problem Solving Skills:
- Machine learning, neural networks, statistical pattern recognition
Byron Shock's Problem Solving Experience:
- I adapted statistically sound testing methodogies for the comparison of multiple machine learning methods on pattern classification problems.
- I developed a method to extend fast orthonormal basis function learning methods to problems of dimensionality three and higher.