Constrained clustering has been well-studied for algorithms like K-means and hierarchical agglomerative clustering. However, how to encode constraints into spectral clustering rem...
The aim of the paper is to introduce general techniques in order to optimize the parallel execution time of sorting on a distributed architectures with processors of various speeds...
We present a constraint-based algorithm for the synthesis of invariants expressed in the combined theory of linear arithmetic and uninterpreted function symbols. Given a set of pro...
Dirk Beyer, Thomas A. Henzinger, Rupak Majumdar, A...
Abstract. Erasure of information incurs an increase in entropy and dissipates heat. Therefore, information-preserving computation is essential for constructing computers that use e...
Background: Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to iden...