We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
In this paper, we study the collision property of one of the robust hash functions proposed in [1]. This method was originally proposed for robust hash generation from blocks of i...
We develop, analyze, and test a training algorithm for support vector machine classifiers without offset. Key features of this algorithm are a new, statistically motivated stoppi...
Because of the complexity of the human structure, and the irregularity of the human tissues, and the discrepancy of human individuality, segmenting and rendering 3D medical data f...
We investigate the following question. Do populations of evolving agents adapt only to their recent environment or do general adaptive features appear over time? We find statistica...