We introduce a parallelized version of tree-decomposition based dynamic programming for solving difficult weighted CSP instances on many cores. A tree decomposition organizes cost ...
MDPs are an attractive formalization for planning, but realistic problems often have intractably large state spaces. When we only need a partial policy to get from a fixed start s...
H. Brendan McMahan, Maxim Likhachev, Geoffrey J. G...
The current framework of reinforcement learning is based on maximizing the expected returns based on scalar rewards. But in many real world situations, tradeoffs must be made amon...
We present preliminary results of a project to create a tuning system that adaptively optimizes programs to the underlying execution platform. We will show initial results from tw...
Abstract— Minimizing the energy cost and improving thermal performance of power-limited datacenters, deploying large computing clusters, are the key issues towards optimizing the...