Multiple Kernel Learning (MKL) can be formulated as a convex-concave minmax optimization problem, whose saddle point corresponds to the optimal solution to MKL. Most MKL methods e...
Zenglin Xu, Rong Jin, Shenghuo Zhu, Michael R. Lyu...
Abstract. The practical utility of optimization technologies is often impacted by factors that reflect how these tools are used in practice, including whether various real-world c...
William E. Hart, Jonathan W. Berry, Erik G. Boman,...
— We consider a queueing system with controllable service rate; for example, a transmitter whose rate can be controlled by varying the transmission power. For such a system we ob...
We present a new technique to examine the trade-off regions of a circuit where its competing performances become “simultaneously optimal”, i.e. Pareto optimal. It is based on ...
In this paper, we present a novel PDE based error concealment algorithm. We formulate the error concealment problem as a sequential optimization problem with both smoothing and or...