Some machine learning models belong to ... predictions can be made by estimating the probability that a given set of inputs belongs to a given class. Hidden Markov Models Markov Chains can be thought ...

The commitment and efforts of artificial intelligence research in network biology are motivated by the fact that machine learning ... a directed graph in the embedded space. To assess this locality ...

Graph kernels are used to transform molecular graphs into fixed-length vectors, which, based on their capacity of measuring similarity, can be used as fingerprints for machine learning (ML ... the ...

Abstract: Outlier detection is a vital preprocessing step in data mining and it holds a great importance for Machine Learning (ML ... is based on the Joint Probability Density Estimation (JPDE) with ...

To address the above issues, we propose a coverless information hiding scheme based on probability graph learning for secure communication in the IoT environment. Instead of modifying an existing ...