We propose a principled account on multiclass spectral clustering. Given a discrete clustering formulation, we first solve a relaxed continuous optimization problem by eigendecomp...
Genetic algorithms (GAs) are multi-dimensional and stochastic search methods, involving complex interactions among their parameters. For last two decades, researchers have been tr...
Boosting is a simple yet powerful modeling technique that is used in many machine learning and data mining related applications. In this paper, we propose a novel scale-space based...
Context-based adaptive entropy coding is an essential feature of modern image compression algorithms; however, the design of these coders is non-trivial due to the balance that mu...
Background: The construction of literature-based networks of gene-gene interactions is one of the most important applications of text mining in bioinformatics. Extracting potentia...