Boosting is a popular way to derive powerful learners from simpler hypothesis classes. Following previous work (Mason et al., 1999; Friedman, 2000) on general boosting frameworks,...
In this work, the tracking analysis of the Normalized Least Mean Fourth (NLMF) algorithm is investigated for a random walk channel under very weak assumptions. The novelty of this...
The problem of low-rank matrix factorization in the presence of missing data has seen significant attention in recent computer vision research. The approach that dominates the lit...
We have developed a new Linear Support Vector Machine (SVM) training algorithm called OCAS. Its computational effort scales linearly with the sample size. In an extensive empirica...
— Average transmission rate and rate oscillation are two important performance metrics for most wireless services. Both are often needed to be optimized in multi-user scheduling ...