Another hybrid conjugate gradient algorithm is subject to analysis. The parameter k is computed as a convex combination of HS k (Hestenes-Stiefel) and DY k (Dai-Yuan) algorithms, i...
We present a globally convergent method for regularized risk minimization problems. Our method applies to Support Vector estimation, regression, Gaussian Processes, and any other ...
The 2-class transduction problem, as formulated by Vapnik [1], involves finding a separating hyperplane for a labelled data set that is also maximally distant from a given set of...
Large-margin structured estimation methods minimize a convex upper bound of loss functions. While they allow for efficient optimization algorithms, these convex formulations are n...
Olivier Chapelle, Chuong B. Do, Quoc V. Le, Alexan...
We develop algorithms for finding the minimum energy transmission schedule for duty-cycle and rate constrained wireless sensor nodes transmitting over an interference channel. Sinc...