A multiclass classification problem can be reduced to a collection of binary problems with the aid of a coding matrix. The quality of the final solution, which is an ensemble of b...
The general approach for automatically driving data collection using information from previously acquired data is called active learning. Traditional active learning addresses the...
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...
This contribution describes a neural network that self-organizes to recover the underlying original sources from typical sensor signals. No particular information is required abou...
—Methods for learning decision rules are being successfully applied to many problem domains, especially where understanding and interpretation of the learned model is necessary. ...