Clustering with constraints is an emerging area of data mining research. However, most work assumes that the constraints are given as one large batch. In this paper we explore the...
This paper proposes a two-step graph partitioning method to discover constrained clusters with an objective function that follows the well-known minmax clustering principle. Compar...
Modern data mining settings involve a combination of attributevalued descriptors over entities as well as specified relationships between these entities. We present an approach t...
M. Shahriar Hossain, Satish Tadepalli, Layne T. Wa...
We present a mixture model whose components are Restricted Boltzmann Machines (RBMs). This possibility has not been considered before because computing the partition function of a...
We present a general framework for the construction of vertex orderings for netlist clustering. Our WINDOW algorithm constructs an ordering by iteratively adding the vertex with h...