3 papers
stat.ML2022
PAC-Bayesian-Like Error Bound for a Class of Linear Time-Invariant Stochastic State-Space Models
Deividas Eringis, John Leth, Zheng-Hua Tan +2
In this paper we derive a PAC-Bayesian-Like error bound for a class of stochastic dynamical systems with inputs, namely, for linear time-invariant stochastic state-space models (st…
math.OC2021
Safe Dynamic Programming
Rafal Wisniewski, Manuela L. Bujorianu
We incorporate safety specifications into dynamic programming. Explicitly, we address the minimization problem of a Markov decision process up to a stopping time with safety constr…
stat.ML2021
PAC-Bayesian theory for stochastic LTI systems
Deividas Eringis, John Leth, Zheng-Hua Tan +3
In this paper we derive a PAC-Bayesian error bound for autonomous stochastic LTI state-space models. The motivation for deriving such error bounds is that they will allow deriving…