In this paper we study the identification of sparse interaction networks as a machine learning problem. Sparsity means that we are provided with a small data set and a high number...
Goele Hollanders, Geert Jan Bex, Marc Gyssens, Ron...
In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either ma...
We start by formulating the resource sharing in peer-to-peer (P2P) networks as a random-matching gift-giving game, where self-interested peers aim at maximizing their own long-ter...
— In this paper, we perform a complete asymptotic performance analysis of the stochastic approximation algorithm (denoted subspace network learning algorithm) derived from Oja’...
Abstract. Vertebrate and most invertebrate organisms interact with their environment through processes of adaptation and learning. Such processes are generally controlled by comple...
Jan Eriksson, Oriol Torres, Andrew Mitchell, Gayle...