1 A kernel determines the inductive bias of a learning algorithm on a specific data set, and it is beneficial to design specific kernel for a given data set. In this work, we propo...
The accurate prediction of program's memory requirements is a critical component in software development. Existing heap space analyses either do not take deallocation into ac...
: Linear subspace analysis (LSA) has become rather ubiquitous in a wide range of problems arising in pattern recognition and computer vision. The essence of these approaches is tha...
We show that a wide class of bidirectional data-flow analyses and program optimizations based on them admit declarative descriptions in the form of type systems. The salient feat...
—A new formulation for multiway spectral clustering is proposed. This method corresponds to a weighted kernel principal component analysis (PCA) approach based on primal-dual lea...