Transfer learning addresses the problem of how to utilize plenty of labeled data in a source domain to solve related but different problems in a target domain, even when the train...
Agents often have to construct plans that obey resource limits for continuous resources whose consumption can only be characterized by probability distributions. While Markov Deci...
The design of computer architectures requires the setting of multiple parameters on which the final performance depends. The number of possible combinations make an extremely huge ...
Pedro A. Castillo, Antonio Miguel Mora, Juan Juli&...
To test large scale socially embedded systems, this paper proposes a multiagent-based participatory design that consists of two steps; 1) participatory simulation, where scenario-...
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...