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A survey on deep learning for cybersecurity: Progress, challenges, and opportunities
As the number of Internet-connected systems rises, cyber analysts find it increasingly difficult
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …
Epidemiological data from the COVID-19 outbreak, real-time case information
Cases of a novel coronavirus were first reported in Wuhan, Hubei province, China, in
December 2019 and have since spread across the world. Epidemiological studies have …
December 2019 and have since spread across the world. Epidemiological studies have …
Machine learning and deep learning frameworks and libraries for large-scale data mining: a survey
The combined impact of new computing resources and techniques with an increasing
avalanche of large datasets, is transforming many research areas and may lead to …
avalanche of large datasets, is transforming many research areas and may lead to …
Machine unlearning of features and labels
Removing information from a machine learning model is a non-trivial task that requires to
partially revert the training process. This task is unavoidable when sensitive data, such as …
partially revert the training process. This task is unavoidable when sensitive data, such as …
Hash layers for large sparse models
We investigate the training of sparse layers that use different parameters for different inputs
based on hashing in large Transformer models. Specifically, we modify the feedforward …
based on hashing in large Transformer models. Specifically, we modify the feedforward …