Reviews: Online and Differentially-Private Tensor Decomposition

STRENGTHS: - The problem addressed by the authors is important - The proposed algorithm is relatively novel and seems effective - While I didn't verify the proofs, the arguments appear correct. WEAKNESSES: - I found the application to differential privacy unconvincing (see comments below) - Experimental validation was a bit light and felt preliminary RECOMMENDATION: I think this paper should be accepted into the NIPS program on the basis of the online algorithm and analysis. However, I think the application to differential privacy, without experimental validation, should be omitted from the main paper in favor of the preliminary experimental evidence of the tensor method. The results on privacy appear too preliminary to appear in a "conference of record" like NIPS. TECHNICAL COMMENTS: 1) Section 1.2: the dimensions of the projection matrices are written as A_i \in \mathbb{R} {m_i \times d_i} .