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Found 3 papers, 1 papers with code
BaTFLED: Bayesian Tensor Factorization Linked to External Data
The vast majority of current machine learning algorithms are designed to predict single responses or a vector of responses, yet many types of response are more naturally organized as matrices or higher-order tensor objects where characteristics are shared across modes.
Localized Data Fusion for Kernel k-Means Clustering with Application to Cancer Biology
In many modern applications from, for example, bioinformatics and computer vision, samples have multiple feature representations coming from different data sources.
Kernelized Bayesian Matrix Factorization
Our algorithm obtains the lowest Hamming loss values on 10 out of 14 multilabel classification data sets compared to five state-of-the-art multilabel learning algorithms.
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