Algorithm 1 Distributed SVOR algorithm

Initialization: initialize hinge loss function weight C, sparsity regularization weight $\alpha$, random approximate dimension D, and total iteration number T. Each node m initializes ${\theta }_m=\{{\mathit{w}}_m,{\mathit{b}}_m\}$. for$k=1:T$    for $m=1:M$       Communication Step: communicate parameters ${\theta }_m$ with neighbors $n\in {\mathcal{N}}_m$.    end for    for $m=1:M$       Combination Step: compute intermediate estimate ${\varphi }_m^k$ via (21).       Computation Step: Compute the subgradients ${\nabla }_{{\mathit{w}}_m}{J}_m\left({\theta }_m^k\right)$, ${\nabla }_{b_{m,q}}{J}_m\left({\theta }_m^k\right)$ via (15) and (16);       Adaption Step: update ${\theta }_m^{k+1}$ via (22).    end for end for