Confidence-Weighted linear classifiers (CW) and its successors were shown to perform well on binary and multiclass NLP problems. In this paper we extend the CW approach for sequen...
Confidence-weighted (CW) learning [6], an online learning method for linear classifiers, maintains a Gaussian distributions over weight vectors, with a covariance matrix that repr...
In this paper, auto regressive (AR) model is applied to error concealment for block-based packet video encoding. Each pixel within the corrupted block is restored as the weighted ...
We present a registration algorithm for pairs of deforming and partial range scans that addresses the challenges of non-rigid registration within a single non-linear optimization....
In recent years, there have been many studies focusing on improving the accuracy of prediction of transmembrane segments, and many significant results have been achieved. In spite...
Jieyue He, Hae-Jin Hu, Robert W. Harrison, Phang C...