In this work we try to bridge the gap often encountered by researchers who find themselves with few or no labeled examples from their desired target domain, yet still have access ...
We present new results from a real-user evaluation of a data-driven approach to learning user-adaptive referring expression generation (REG) policies for spoken dialogue systems. ...
We investigate the problem of learning action effects in partially observable STRIPS planning domains. Our approach is based on a voted kernel perceptron learning model, where act...
Link prediction is a key technique in many applications such as recommender systems, where potential links between users and items need to be predicted. A challenge in link predic...
A critical success factor in Insurance business is its ability to use information sources and contained knowledge in the most effective way. Its profitability is obtained through t...
Andrea Tettamanzi, Luca Sammartino, Mikhail Simono...