We extend the VC theory of statistical learning to data dependent spaces of classifiers. This theory can be viewed as a decomposition of classifier design into two components; the...
Adam Cannon, J. Mark Ettinger, Don R. Hush, Clint ...
We present a novel postprocessing utility called adaptive geometry image (AGIM) for global parameterization techniques that can embed a 3D surface onto a rectangular1 domain. This ...
Abstract— Enabling mobile robots to assemble large structures in constrained environments requires planning systems that are both capable of dealing with high complexity and can ...
Abstract--A crucial issue in designing learning machines is to select the correct model parameters. When the number of available samples is small, theoretical sample-based generali...
The strong cross-correlation that exists between the two input audio channels makes the problem of stereophonic acoustic echo cancellation (AEC) complex and challenging to solve. R...