We study similarity queries for time series data where similarity is defined in terms of a set of linear transformations on the Fourier series representation of a sequence. We ha...
FBRAM, a new form of dynamic random access memory that greatly accelerates the rendering of Z-buffered primitives, is presented. Two key concepts make this acceleration possible. ...
Michael F. Deering, Stephen A. Schlapp, Michael G....
There are two main approaches to the problem of gender classification, Support Vector Machines (SVMs) and Adaboost learning methods, of which SVMs are better in correct rate but ar...
We present an approach to music identification based on weighted finite-state transducers and Gaussian mixture models, inspired by techniques used in large-vocabulary speech recogn...
We address the problem of learning the mapping between words and their possible pronunciations in terms of sub-word units. Most previous approaches have involved generative modeli...