Abstract. Inverse reinforcement learning addresses the general problem of recovering a reward function from samples of a policy provided by an expert/demonstrator. In this paper, w...
This paper presents novel low-voltage high order single loop sigma-delta modulator structures for wideband applications. The proposed architectures employ the technique of double-...
A statistical algorithm was developed for the damage fault diagnosis and prognosis tool and the present work focuses on the experimental validation. The oxide scale growth experim...
One significant problem in tile-based texture synthesis is the presence of conspicuous seams in the tiles. The reason is that the sample patches employed as primary patterns of t...
We present a simple, agnostic active learning algorithm that works for any hypothesis class of bounded VC dimension, and any data distribution. Our algorithm extends a scheme of C...