Hello all,

I need some theoretical pointers (formulas, articles, online links) on how to merge Singular Value Decompositions (SVD) of two matrices (two different sets of observations over the same set of features).

That is, I have two SVDs: $A=U_A*S_A*V^T_A$ and $B=U_B*S_B*V^T_B$ and want to know SVD $A|B=U_{A|B}*S_{A|B}*V_{A|B}$. The original matrices $A$ and $B$ are unavailable, the solution must make use of the $U_A, S_A, V_A, U_B, S_B, V_B$ matrices only.

I need this because I want to implement a distributed version of incremental SVD: have several computation nodes work on different sets of observations independently, and then merge their results into one.

Cheers!