The proposed LP filter is fundamentally different from previous weighted

Due to space constraints we only address major concerns; all suggestions will be included in the final version. Experimentally we've observed that when using previous weighted We will compare and cite related work (gTop-k) in the final draft. In sec.3 we assume min. SGD has a small critical batch size to approximate a full gradient descent iteration, no matter the size of dataset. Appendix-F shows ScaleCom's scalability in system performance; more Analogously, we perform filtering on the residual gradients (see eq.(5)) Connection will be discussed in the revised version.