We develop a novel online learning algorithm for the group lasso in order to efficiently find the important explanatory factors in a grouped manner. Different from traditional bat...
Haiqin Yang, Zenglin Xu, Irwin King, Michael R. Ly...
In this paper, we propose a low-power testing methodology for the scan-based BIST. A smoother is included in the test pattern generator (TPG) to reduce average power consumption d...
In an online linear optimization problem, on each period t, an online algorithm chooses st S from a fixed (possibly infinite) set S of feasible decisions. Nature (who may be adve...
We consider the problem of rate and power allocation in a multiple-access channel. Our objective is to obtain rate and power allocation policies that maximize a general concave ut...
Ali ParandehGheibi, Atilla Eryilmaz, Asuman E. Ozd...
Background: Baum-Welch training is an expectation-maximisation algorithm for training the emission and transition probabilities of hidden Markov models in a fully automated way. I...