Abstract. Most classification methods assume that the samples are drawn independently and identically from an unknown data generating distribution, yet this assumption is violated ...
A dozen people who cannot speak and have very limited voluntary muscle control because of cerebral palsy or traumatic brain injury have tried using a new technology called the Cam...
The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...
Francis R. Bach, Romain Thibaux, Michael I. Jordan
Computing is moving toward a pervasive context-aware environment in which agents with limited resources will require external support to help them become context-aware. In this pa...
In [4], Freuderdefines several types of interchangeability to capture the equivalenceamongthe valuesof a variable in a discrete constraint satisfaction problem(CSP), and provides ...