Complexity of Classical Acceleration for -Regularized PageRank
- LLMSV
We study the degree-weighted work required to compute -regularized PageRank using the standard accelerated proximal-gradient method (FISTA). For non-accelerated methods (ISTA), the best known worst-case work is , where is the teleportation parameter and is the -regularization parameter. It is not known whether classical acceleration methods can improve to while preserving the locality scaling, or whether they can be asymptotically worse. For FISTA, we show a negative result by constructing a family of instances for which standard FISTA is asymptotically worse than ISTA. On the positive side, we analyze FISTA on a slightly over-regularized objective and show that, under a confinement condition, all spurious activations remain inside a boundary set . This yields a bound consisting of an accelerated term plus a boundary overhead . We also provide graph-structural sufficient conditions that imply such confinement.
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