We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...
Dimensionalitycurse and dimensionalityreduction are two issues that have retained highinterest for data mining, machine learning, multimedia indexing, and clustering. We present a...
Caetano Traina Jr., Agma J. M. Traina, Leejay Wu, ...
An alternative method to H.263 for encoding of moving images at bit rates below 64 kbit/s is presented using adaptive spatial subsampling, mesh based interpolation and node tracki...
We present a system for describing and solving closed queuing network models of the memory access performance of NUMA architectures. The system consists of a model description lan...
We address the problem of automatically acquiring case frame patterns (selectional patterns) from large corpus data. In particular, we l)ropose a method of learning dependencies b...