Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
The Apriori algorithm is a fundamental correlation-based data mining kernel used in a variety of fields. The innovation in this paper is a highly parallel custom architecture impl...
In the paper we present new Alternating Least Squares (ALS) algorithms for Nonnegative Matrix Factorization (NMF) and their extensions to 3D Nonnegative Tensor Factorization (NTF) ...
Leveraging the power of nowadays graphics processing units for robust power grid simulation remains a challenging task. Existing preconditioned iterative methods that require inco...
Performance analysis tools are critical for the effective use of large parallel computing resources, but existing tools have failed to address three problems that limit their scal...