In this paper, we propose a new data reduction algorithm that iteratively selects some samples and ignores others that can be absorbed, or represented, by those selected. This alg...
This paper presents a class of algorithms suitable for model reduction of distributed systems. Distributed systems are not suitable for treatment by standard model-reduction algor...
We propose a new lattice reduction method. Our algorithm approximates shortest lattice vectors up to a factor ≤ (k/6)n/2k and makes use of Grover’s quantum search algorithm. Th...
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
Evan Greensmith, Peter L. Bartlett, Jonathan Baxte...
Abstract. Partial order reduction limits the state explosion problem that arises in model checking by limiting the exploration of redundant interleavings. A state space search algo...