Refereed full papers (journals, book chapters, international conferences)

2001

@article{PeB2001,
	vgclass =	{refpap},
	author =	{Jing Peng and Bir Bhanu},
	title =	{Local discriminative learning for pattern recognition},
	journal =	{Pattern Recognition},
	volume =	{34},
	number =	{1},
	pages =	{139--150},
	month =	{January},
	year =	{2001},
	url =	{http://dx.doi.org/10.1016/S0031-3203(99)00209-5},
	abstract =	{Local discriminative learning methods approximate a target
	function (a posteriori class probability function) directly by
	partitioning the feature space into a set of local regions, and
	appropriately modeling a simple input-output relationship (function) in
	each one. This paper presents a new method for judiciously partitioning
	the input feature space in order to accurately represent the target
	function. The method accomplishes this by approximating not only the
	target function itself but also its derivatives. As such, the method
	partitions the input feature space along those dimensions for which the
	class probability function changes most rapidly, thus minimizing bias.
	The efficacy of the method is validated using a variety of simulated
	and real-world data.},
}