This paper proposes the kernel orthogonal mutual subspace method (KOMSM) for 3D object recognition. KOMSM is a kernel-based method for classifying sets of patterns such as video fr...
We describe an ensemble learning approach that accurately learns from data that has been partitioned according to the arbitrary spatial requirements of a large-scale simulation whe...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...
We present a method which uses example pairs of equal or unequal class labels to select a subspace with near optimal metric properties in a kernel-induced Hilbert space. A represen...
We examine scattered hairpins, which are structures formed when a single strand of nucleotides folds into a partially hybridized stem and a loop. To specify different classes of h...
In this paper, we introduce Applicative functors--an abstract characterisation of an applicative style of effectful programming, weaker than Monads and hence more widespread. it i...