With very noisy data, having plentiful samples eliminates overfitting in nonlinear regression, but not in nonlinear principal component analysis (NLPCA). To overcome this problem...
We introduce a new method that characterizes typical local image features (e.g., SIFT [9], phase feature [3]) in terms of their distinctiveness, detectability, and robustness to i...
The ability to predict which files in a large software system are most likely to contain the largest numbers of faults in the next release can be a very valuable asset. To accomp...
Thomas J. Ostrand, Elaine J. Weyuker, Robert M. Be...
In this paper we analyze the problem of estimating a function from different noisy data sets collected by spatially distributed sensors and subject to unknown temporal shifts. We p...
Aspects are intended to add needed functionality to a system or to treat concerns of the system by augmenting or changing the existing code in a manner that cross-cuts the usual c...