We have extensive experience with distributed facilitation of synchronous virtual meetings since 1992. More recently, we have gained experience in asynchronous virtual meetings an...
Michael McQuaid, Robert O. Briggs, Duffy Gillman, ...
Abstract. A successful approach to tracking is to on-line learn discriminative classifiers for the target objects. Although these trackingby-detection approaches are usually fast a...
Christian Leistner, Martin Godec, Amir Saffari, Ho...
We develop a novel online learning algorithm for the group lasso in order to efficiently find the important explanatory factors in a grouped manner. Different from traditional bat...
Haiqin Yang, Zenglin Xu, Irwin King, Michael R. Ly...
Detecting abnormal behaviors in crowd scenes is quite important for public security and has been paid more and more attentions. Most previous methods use offline trained model to p...
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...