We extend the VC theory of statistical learning to data dependent spaces of classifiers. This theory can be viewed as a decomposition of classifier design into two components; the...
Adam Cannon, J. Mark Ettinger, Don R. Hush, Clint ...
We present a new method to robustly and efficiently analyze foreground when we detect background for a fixed camera view by using mixture of Gaussians models and multiple cues. Th...
String kernels which compare the set of all common substrings between two given strings have recently been proposed by Vishwanathan & Smola (2004). Surprisingly, these kernels...
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Glo...
We consider the problem of computing the Euclidean projection of a vector of length n onto a closed convex set including the 1 ball and the specialized polyhedra employed in (Shal...