In this paper, we address two issues of long-standing interest in the reinforcement learning literature. First, what kinds of performance guarantees can be made for Q-learning aft...
— This paper describes an approach to cooperative localization which finds its roots in robust estimation, employing an unknown-but-bounded error model for sensor measurements. ...
The mapping between syntactic structure and prosodic structure is a widely discussed topic in linguistics. In this work we use insights gained from research on syntax-to-prosody m...
We consider the problem of optimal position liquidation with the aim of maximizing the expected cash flow stream from the transaction in the presence of temporary or permanent ma...
A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a ...