We consider the problem of learning a similarity function from a set of positive equivalence constraints, i.e. 'similar' point pairs. We define the similarity in informa...
We propose a novel linearly augmented tree method for efficient scale and rotation invariant object matching. The proposed method enforces pairwise matching consistency defined ...
We introduce a learning algorithm for the weights in a very common class of discrimination functions usually called weighted average". Di erent submodules are produced by som...
We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
In familiar design domains, expert designers are able to quickly focus on “good designs”, based on constraints they have learned while exploring the design space. This ability ...