Generative kernels represent theoretically grounded tools able to increase the capabilities of generative classification through a discriminative setting. Fisher Kernel is the fi...
Manuele Bicego, Marco Cristani, Vittorio Murino, E...
One of the main research concern in neural networks is to find the appropriate network size in order to minimize the trade-off between overfitting and poor approximation. In this ...
To deal with the issue of data unbalanced condition among a task of multilingual speech recognition and a phenomenon of pronunciation variations across languages, we propose an ap...
In order to better protect and conserve biodiversity, ecologists use machine learning and statistics to understand how species respond to their environment and to predict how they...
We introduce a robust and efficient framework called CLUMP (CLustering Using Multiple Prototypes) for unsupervised discovery of structure in data. CLUMP relies on finding multip...