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Found 4 papers, 1 papers with code
Federated Learning for Sparse Principal Component Analysis
The federated learning framework addresses this challenge.
Semi-Supervised Learning via Clustering Representation Space
We proposed a novel loss function that combines supervised learning with clustering in deep neural networks.
Anomaly Detection via oversampling Principal Component Analysis
Based on this idea, an over-sampling principal component analysis outlier detection method is proposed for emphasizing the influence of an abnormal instance (or an outlier).
Ranked #1 on
Anomaly Detection
on kdd 99
Periodic Step Size Adaptation for Single Pass On-line Learning
It has been established that the second-order stochastic gradient descent (2SGD) method can potentially achieve generalization performance as well as empirical optimum in a single pass (i. e., epoch) through the training examples.
