A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Analog video digitized from noisy sources can suffer of line registration problems due to bad synchronization pulses. The effect is that the image lines are randomly shiftedwith r...
Maximum Margin Matrix Factorization (MMMF) was recently suggested (Srebro et al., 2005) as a convex, infinite dimensional alternative to low-rank approximations and standard facto...
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
Conventional similarity metrics used to sustain diversity in evolving populations are not well suited to sequential decision tasks. Genotypes and phenotypic structure are poor pre...