We present a classification algorithm built on our adaptation of the Generalized Lotka-Volterra model, well-known in mathematical ecology. The training algorithm itself consists ...
Karen Hovsepian, Peter Anselmo, Subhasish Mazumdar
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
Classical statistical learning theory studies the generalisation performance of machine learning algorithms rather indirectly. One of the main detours is that algorithms are studi...
In this paper, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define parallel discriminant hyperplanes for the ordinal ...
We study the weight dynamics of the floating-gate pFET synapse and the effects of the pFET's gate and drain voltages on these dynamics. We show that we can derive a weight upd...