Task-selection policies are critical to the performance of any architecture that uses speculation to extract parallel tasks from a sequential thread. This paper demonstrates that ...
Mayank Agarwal, Kshitiz Malik, Kevin M. Woley, Sam...
This paper describes a method of supervised learning based on forward selection branching. This method improves fault tolerance by means of combining information related to general...
When monitoring spatial phenomena, which can often be modeled as Gaussian processes (GPs), choosing sensor locations is a fundamental task. There are several common strategies to ...
This paper deals with a stochastic Generalized Assignment Problem with recourse. Only a random subset of the given set of jobs will require to be actually processed. An assignment...
Maria Albareda-Sambola, Maarten H. van der Vlerk, ...
Classification algorithms typically induce population-wide models that are trained to perform well on average on expected future instances. We introduce a Bayesian framework for l...