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 address the problem of learning distance metrics using side-information in the form of groups of "similar" points. We propose to use the RCA algorithm, which is a sim...
Abstract. We present a novel algorithm called DBSC, which finds subspace clusters in numerical datasets based on the concept of ”dependency”. This algorithm employs a depth-...
In fuzzy clustering, the fuzzy c-means (FCM) algorithm is the best known and most used method. Although FCM is a very useful method, it is sensitive to noise and outliers so that W...
The core computation in BDD-based symbolic synthesis and verification is forming the image and pre-image of sets of states under the transition relation characterizing the sequen...