We present a method for dependency grammar induction that utilizes sparse annotations of semantic relations. This induction set-up is attractive because such annotations provide u...
Industrial applications use specific problem-oriented implementations of large sparse and irregular data structures. Hence there is a need for tools that make it possible for deve...
Implicit surface is a well-known surface representation. Geometric details of an object can be represented using less surface primitives than other representations such as polygon...
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semisupervised manner: the model is learnt from example ...
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...