In this paper, we present an original framework to model frame semantic resources (namely, FrameNet) using minimal supervision. This framework can be leveraged both to expand an e...
Marco Pennacchiotti, Diego De Cao, Paolo Marocco, ...
We address the task of computing vector space representations for the meaning of word occurrences, which can vary widely according to context. This task is a crucial step towards ...
Tuning SVM hyperparameters is an important step in achieving a high-performance learning machine. It is usually done by minimizing an estimate of generalization error based on the...
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...
In this paper we propose a classification-based method towards the segmentation of diffusion tensor images. We use Support Vector Machines to classify diffusion tensors and we ex...