We present a unifying framework for information theoretic feature selection, bringing almost two decades of research on heuristic filter criteria under a single theoretical inter...
Gavin Brown, Adam Pocock, Ming-Jie Zhao, Mikel Luj...
Abstract-- In evolutionary algorithms, the fitness of a population increases with time by mutating and recombining individuals and by a biased selection of more fit individuals. Th...
Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being...
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Y...
This paper proposes an integrated approach to arrive at optimal build orientations, simultaneously minimizing surface roughness ‘Ra’ and build time ‘T’, for object manufac...
We propose a practical path-based framework for deriving and simplifying source-tracking information for term unification in the empty theory. Such a framework is useful for debugg...