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,...
Bayesian network is a widely used tool for data analysis, modeling and decision support in various domains. There is a growing need for techniques and tools which can automatically...
—String matching is a ubiquitous problem that arises in a wide range of applications in computing, e.g., packet routing, intrusion detection, web querying, and genome analysis. D...
Motions can occur over both short and long time scales. We introduce motion denoising, which treats short-term changes as noise, long-term changes as signal, and rerenders a video...
Dictionary learning is a challenging theme in computer vision. The basic goal is to learn a sparse representation from an overcomplete basis set. Most existing approaches employ a...