Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices

ICML 2018 Zengfeng Huang

Given a large matrix $A\in\real^{n\times d}$, we consider the problem of computing a sketch matrix $B\in\real^{\ell\times d}$ which is significantly smaller than but still well approximates $A$. We are interested in minimizing the covariance error $\norm{A^TA-B^TB}_2.$We consider the problems in the streaming model, where the algorithm can only make one pass over the input with limited working space... (read more)

PDF Abstract


No code implementations yet. Submit your code now


Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.