We introduce a new algorithm based on linear programming that approximates the differential value function of an average-cost Markov decision process via a linear combination of p...
Current trends suggest future software systems will rely on service-discovery protocols to combine and recombine distributed services dynamically in reaction to changing condition...
Christopher Dabrowski, Kevin L. Mills, Andrew L. R...
As the scale of high-performance computing (HPC) continues to grow, failure resilience of parallel applications becomes crucial. In this paper, we present FT-Pro, an adaptive fault...
The focus of this paper is on how to select a small sample of examples for labeling that can help us to evaluate many different classification models unknown at the time of sampl...
A linear programming technique is introduced that jointly performs feature selection and classifier training so that a subset of features is optimally selected together with the c...