Abstract. Successful multi-target tracking requires locating the targets and labeling their identities. This mission becomes significantly more challenging when many targets freque...
Transfer learning allows leveraging the knowledge of source domains, available a priori, to help training a classifier for a target domain, where the available data is scarce. Th...
We developed Gr?mlin 2.0, a new multiple network aligner with (1) a novel scoring function that can use arbitrary features of a multiple network alignment, such as protein deletion...
Jason Flannick, Antal F. Novak, Chuong B. Do, Bala...
Learning general truths from the observation of simple domains and, further, learning how to use this knowledge are essential capabilities for any intelligent agent to understand ...
Paulo Santos, Derek R. Magee, Anthony G. Cohn, Dav...
We present a multi-label multiple kernel learning (MKL) formulation in which the data are embedded into a low-dimensional space directed by the instancelabel correlations encoded ...