Learning Tensor Latent Features
arXiv: Learning, Volume abs/1810.04754, 2018.
We study the problem of learning latent feature models (LFMs) for tensor data commonly observed in science and engineering such as hyperspectral imagery. However, the problem is challenging not only due to the non-convex formulation, the combinatorial nature of the constraints in LFMs, but also the high-order correlations in the data. In ...More
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