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 ...
—We formulate the service composition problem as a multi-objective stochastic program which simultaneously optimizes the following quality of service (QoS) parameters: workflow ...
The problem of computing a maximum a posteriori (MAP) configuration is a central computational challenge associated with Markov random fields. There has been some focus on “tr...
Pradeep Ravikumar, Alekh Agarwal, Martin J. Wainwr...
We prove the existence of an algorithm A for computing 2-d or 3-d convex hulls that is optimal for every point set in the following sense: for every set S of n points and for ever...
We study the question of how to easily recognize whether a social unction f from an abstract type space to a set of outcomes is truthful, i.e. implementable by a truthful mechanis...