This paper reviews the recent surge of interest in convex optimization in a context of pattern recognition and machine learning. The main thesis of this paper is that the design of...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...
As networks grow in size and complexity, network management has become an increasingly challenging task. Many protocols have tunable parameters, and optimization is the process of...
—This paper presents a new method developed for the optimal design of microrobotic compliant mechanisms. It is based on a flexible building block method, called FlexIn, which use...
Numerical design optimization algorithms are highly sensitive to the particular formulation of the optimization problems they are given. The formulation of the search space, the o...
Thomas Ellman, John Keane, Takahiro Murata, Mark S...
Recent advances in statistical inference and machine learning close the divide between simulation and classical optimization, thereby enabling more rigorous and robust microarchit...