Abstract. Traditional stochastic programming is risk neutral in the sense that it is concerned with the optimization of an expectation criterion. A common approach to addressing ri...
We consider the task of devising large-margin based surrogate losses for the learning to rank problem. In this learning to rank setting, the traditional hinge loss for structured ...
Successful software maintenance is becoming increasingly critical due to the increasing dependence of our society and economy on software systems. One key problem of software main...
We discuss the use in machine learning of a general type of convex optimisation problem known as semi-definite programming (SDP) [1]. We intend to argue that SDP’s arise quite n...
With an ever-increasing portion of the delay in highspeed CMOS chips attributable to the interconnect, interconnect-circuit design automation continues to grow in importance. By t...