We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
In this paper, we propose a new face hallucination framework based on image patches, which integrates two novel statistical super-resolution models. Considering that image patches...
The application of boosting technique to the regression problems has received relatively little attention in contrast to the research aimed at classification problems. This paper ...
Significant changes in the instance distribution or associated cost function of a learning problem require one to reoptimize a previously-learned classifier to work under new cond...
Chris Bourke, Kun Deng, Stephen D. Scott, Robert E...
We introduce FuncICA, a new independent component analysis method for pattern discovery in inherently functional data, such as time series data. FuncICA can be considered an analo...