Provable Sparse Tensor Decomposition

Understand

We propose a novel sparse tensor decomposition method, namely Tensor Truncated Power (TTP) method, that incorporates variable selection into the estimation of decomposition components.

• The sparsity is achieved via an efficient truncation step embedded in the tensor power iteration.
• Our method applies to a broad family of high dimensional latent variable models, including high dimensional Gaussian mixture and mixtures of sparse regressions.
• A thorough theoretical investigation is further conducted.