In this paper, we propose a number of adaptive prototype learning (APL) algorithms. They employ the same algorithmic scheme to determine the number and location of prototypes, but...
In this work a new online learning algorithm that uses automatic relevance determination (ARD) is proposed for fast adaptive nonlinear filtering. A sequential decision rule for i...
Thomas Buchgraber, Dmitriy Shutin, H. Vincent Poor
This paper proposes a methodology to generate artificial data sets to evaluate the behavior of machine learning techniques. The methodology relies in the definition of a domain an...
Joaquin Rios-Boutin, Albert Orriols-Puig, Josep Ma...
With a few exceptions, discriminative training in statistical machine translation (SMT) has been content with tuning weights for large feature sets on small development data. Evid...
We investigate the problem of non-covariant behavior of policy gradient reinforcement learning algorithms. The policy gradient approach is amenable to analysis by information geom...