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Leaving out neural networks and deep learning, which require a much higher level of computing resources, the most common algorithms are Naive Bayes, Decision Tree, Logistic Regression, K-Nearest ...
Of all the excellent machine learning and deep learning frameworks available, TensorFlow is the most mature, has the most citations in research papers (even excluding citations from Google ...
Combining graphs and machine learning has been getting a lot of attention lately, especially since the work published by researchers from DeepMind, Google Brain, MIT, and the University of Edinburgh.
This paper addresses the challenge of classifying Internet of Things (IoT) binary files as either malware or benign using graph-theoretical features derived from Control Flow Graphs (CFGs). We use a ...
The paper, "Relational inductive biases, deep learning, and graph networks," posted on the arXiv pre-print service, is authored by Peter W. Battaglia of Google's DeepMind unit, along with ...
This paper addresses the challenge of classifying Internet of Things (IoT) binary files as either malware or benign using graph-theoretical features derived from Control Flow Graphs (CFGs). We use a ...