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...
The study of self-replicating structures in Computer Science has been taking place for more than half a century, motivated by the desire to understand the fundamental principles a...
Increasingly large amount of multidimensional data are being generated on a daily basis in many applications. This leads to a strong demand for learning algorithms to extract usef...
Haiping Lu, Konstantinos N. Plataniotis, Anastasio...
Levin introduced an average-case complexity measure, based on a notion of \polynomialon average," and de ned \average-case polynomial-time many-one reducibility" amongra...
This paper presents a segmentation-based handwriting recognizer and the performance that it achieves on the numerical fields extracted from a large single-writer historical collec...
Marius Bulacu, Axel Brink, Tijn van der Zant, Lamb...