We study the problem of learning regular tree languages from text. We show that the framework of function distinguishability as introduced by the author in Theoretical Computer Sc...
In this paper, on-line training of neural networks is investigated in the context of computer-assisted colonoscopic diagnosis. A memory-based adaptation of the learning rate for t...
George D. Magoulas, Vassilis P. Plagianakos, Micha...
To navigate in unknown environments, mobile robots require the ability to build their own maps. A major problem for robot map building is that odometry-based dead reckoning cannot ...
Policy gradient (PG) reinforcement learning algorithms have strong (local) convergence guarantees, but their learning performance is typically limited by a large variance in the e...
We consider a general class of regularization methods which learn a vector of parameters on the basis of linear measurements. It is well known that if the regularizer is a nondecr...
Andreas Argyriou, Charles A. Micchelli, Massimilia...