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Chapter and Conference Paper
Towards Sparsified Federated Neuroimaging Models via Weight Pruning
Federated training of large deep neural networks can often be restrictive due to the increasing costs of communicating the updates with increasing model sizes. Various model pruning techniques have been design...
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Chapter and Conference Paper
A New Neighborhood-Based Outlier Detection Technique
Outlier detection is one of the most vital and essential issues in data mining tasks. We propose a new method to detect and analyze outliers. We apply neighborhood-based outlier detection technique to detect a...
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Chapter and Conference Paper
DeepFP for Finding Nash Equilibrium in Continuous Action Spaces
Finding Nash equilibrium in continuous action spaces is a challenging problem and has applications in domains such as protecting geographic areas from potential attackers. We present DeepFP, an approximate ext...