Many collective labeling tasks require inference on graphical models where the clique potentials depend only on the number of nodes that get a particular label. We design efficien...
Traditional non-parametric statistical learning techniques are often computationally attractive, but lack the same generalization and model selection abilities as state-of-the-art...
Kernel methods have gained a great deal of popularity in the machine learning community as a method to learn indirectly in highdimensional feature spaces. Those interested in rela...
Animal development can be described as a complex, threedimensional cellular system that changes dramatically across time as a consequence of cell proliferation, differentiation an...
Stephan Preibisch, Radoslaw Ejsmont, Torsten Rohlf...
Satisfiability of complex word-level formulas often arises as a problem in formal verification of hardware designs described at the register transfer level (RTL). Even though most...