1 This paper provides a new, generalized approach to the problem of encoding information as vectors of binary digits. We furnish a formal definition for the Boolean constrained enc...
We present a novel framework for multi-label learning that explicitly addresses the challenge arising from the large number of classes and a small size of training data. The key a...
Most prior theoretical research on partitioning algorithms for real-time multiprocessor platforms has focused on ensuring that the cumulative computing requirements of the tasks a...
Nathan Fisher, James H. Anderson, Sanjoy K. Baruah
Abstract One of the goals envisioned by Grid computing is to make the execution of both computational and data-intensive problems possible. A key problem is finding the optimal set...
Marc De Leenheer, Pieter Thysebaert, Bruno Volckae...
Data clustering is a difficult problem due to the complex and heterogeneous natures of multidimensional data. To improve clustering accuracy, we propose a scheme to capture the lo...