We introduce a general formulation, called non-negative graph embedding, for non-negative data decomposition by integrating the characteristics of both intrinsic and penalty graph...
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
Existing profile-guided partial redundancy elimination (PRE) methods use speculation to enable the removal of partial redundancies along more frequently executed paths at the expe...
We present an efficient colon flattening algorithm using conformal structure, which is angle-preserving and minimizes the global distortion. Moreover, our algorithm is general w...
The popular bag-of-features representation for object recognition collects signatures of local image patches and discards spatial information. Some have recently attempted to at l...