Investments in innovative technologies face uncertainties and are often made in stages. We develop a multi-period game-theoretical model where the potential of a new technology is...
Traditional machine learning makes a basic assumption: the training and test data should be under the same distribution. However, in many cases, this identicaldistribution assumpt...
As any other problem solving task that employs search, AI Planning needs heuristics to efficiently guide the problem-space exploration. Machine learning (ML) provides several tec...
Learning object categories from small samples is a challenging problem, where machine learning tools can in general provide very few guarantees. Exploiting prior knowledge may be ...
Tatiana Tommasi, Francesco Orabona, Barbara Caputo
Abstract. This paper introduces the notion of Run Transferable Libraries, a mechanism to pass knowledge acquired in one GP run to another. We demonstrate that a system using these ...