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Found 3 papers, 2 papers with code
Analytical Characterization and Design Space Exploration for Optimization of CNNs
Moving data through the memory hierarchy is a fundamental bottleneck that can limit the performance of core algorithms of machine learning, such as convolutional neural networks (CNNs).
PL-NMF: Parallel Locality-Optimized Non-negative Matrix Factorization
Non-negative Matrix Factorization (NMF) is a key kernel for unsupervised dimension reduction used in a wide range of applications, including topic modeling, recommender systems and bioinformatics.
ATP: Directed Graph Embedding with Asymmetric Transitivity Preservation
Directed graphs have been widely used in Community Question Answering services (CQAs) to model asymmetric relationships among different types of nodes in CQA graphs, e. g., question, answer, user.
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