Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
Despite steady research advances in many aspects of virtual reality, building and testing virtual worlds remains to be a very difficult process. Most virtual environments are stil...
—In this paper, we investigate data parallelism in exact inference with respect to arbitrary junction trees. Exact inference is a key problem in exploring probabilistic graphical...
In this paper, we focus on efficiently achieving Proportional Delay Differentiation (PDD), an instance of the Proportional Differentiation Model (PDM) first proposed under the Dif...
Quantile regression refers to the process of estimating the quantiles of a conditional distribution and has many important applications within econometrics and data mining, among ...
Novi Quadrianto, Kristian Kersting, Mark D. Reid, ...