Abstract. In this paper, we propose new adaptive local refinement (ALR) strategies for firstorder system least-squares (FOSLS) finite element in conjunction with algebraic multi...
J. H. Adler, Thomas A. Manteuffel, Stephen F. McCo...
Document clustering has long been an important problem in information retrieval. In this paper, we present a new clustering algorithm ASI1, which uses explicitly modeling of the s...
For many large-scale combinatorial search/optimization problems, meta-heuristic algorithms face noisy objective functions, coupled with computationally expensive evaluation times....
Memory interleaving is a cost-efficient approach to increase bandwidth. Improving data access locality and reducing memory access conflicts are two important aspects to achieve hi...
Estimation of Distribution Algorithms (EDAs) are a class of evolutionary algorithms that use machine learning techniques to solve optimization problems. Machine learning is used t...