Most connectionist research has focused on learning mappings from one space to another (eg. This paper introduces the more general task of learning constraint surfaces. It describes a simple but powerful architecture for learning and manipulating nonlinear surfaces from data. We demonstrate the technique on low dimensional synthetic surfaces and compare it to nearest neighbor approaches. We then show its utility in learning the space of lip images in a system for improving speech recognition by lip reading.

In instruction, two general methodologies lead understudies towards their schooling -- profound and surface learning. Man has five fundamental requests in their life. Training is one of them. Man can learn at whatever stage in life. All aspects of your life have numerous things to learn.

Most connectionist research has focused on learning mappings from one space to another (eg.

Most connectionist research has focused on learning mappings from one space to another (eg.

Most connectionist research has focused on learning mappings from one space to another (eg.