Efficient Numerical Methods to Solve Sparse Linear Equations with Application to PageRank

Understand

In this paper, we propose three methods to solve the PageRank problem for the transition matrices with both row and column sparsity.

• Our methods reduce the PageRank problem to the convex optimization problem over the simplex.
• The first algorithm is based on the gradient descent in L1 norm instead of the Euclidean one.
• The second algorithm extends the Frank-Wolfe to support sparse gradient updates.