: This paper addresses the inference of probabilistic classification models using weakly supervised learning. The main contribution of this work is the development of learning meth...
We previously proposed a decoding method for automatic speech recognition utilizing hypothesis scores weighted by voice activity detection (VAD)-measures. This method uses two Gau...
We describe a new method for pruning in dynamic models based on running an adaptive filtering algorithm online during decoding to predict aspects of the scores in the near future....
This paper proposes a framework for agent-based distributed machine learning and data mining based on (i) the exchange of meta-level descriptions of individual learning processes ...
Truly ubiquitous computing poses new and significant challenges. A huge number of heterogeneous devices will interact to perform complex distributed tasks. One of the key aspects...
Nicola Bicocchi, Marco Mamei, Andrea Prati, Rita C...