Abstract. Most correlation clustering algorithms rely on principal component analysis (PCA) as a correlation analysis tool. The correlation of each cluster is learned by applying P...
We introduce an algorithm for approximating a 2manifold 3D mesh by a set of developable surfaces. Each developable surface is a generalized cylinder represented as a strip of tria...
Most machine learning algorithms are designed either for supervised or for unsupervised learning, notably classification and clustering. Practical problems in bioinformatics and i...
In distributed-memory message-passing architectures reducing communication cost is extremely important. In this paper, we present a technique to optimize communication globally. O...
Mahmut T. Kandemir, Prithviraj Banerjee, Alok N. C...
In a constraint-drivenlayout synthesisenvironment,parasitic constraints are generated and implemented in each phase of the design process to meet a given set of performance specif...
Edoardo Charbon, Paolo Miliozzi, Enrico Malavasi, ...