MP2SDA: Multi-Party Parallelized Sparse Discriminant Learning
ACM Transactions on Knowledge Discovery from Data, pp. 1-22, 2020.
Sparse Discriminant Analysis (SDA) has been widely used to improve the performance of classical Fisher’s Linear Discriminant Analysis in supervised metric learning, feature selection, and classification. With the increasing needs of distributed data collection, storage, and processing, enabling the Sparse Discriminant Learning to embrace ...More
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