Complexity of Classical Acceleration for $\ell_1$-Regularized PageRank
Abstract
We study the degree-weighted work required to compute -regularized PageRank using the standard one-gradient-per-iteration accelerated proximal-gradient method (FISTA). For non-accelerated local methods, the best known worst-case work scales as , where is the teleportation parameter and is the -regularization parameter. A natural question is whether FISTA can improve the dependence on from to while preserving the locality scaling. The challenge is that acceleration can break locality by transiently activating nodes that are zero at optimality, thereby increasing the cost of gradient evaluations. We analyze FISTA on a slightly over-regularized objective and show that, under a checkable confinement condition, all spurious activations remain inside a boundary set . This yields a bound consisting of an accelerated term plus a boundary overhead . We provide graph-structural conditions that imply such confinement. Experiments on synthetic and real graphs show the resulting speedup and slowdown regimes under the degree-weighted work model.
Source: arXiv:2602.21138v1 - http://arxiv.org/abs/2602.21138v1 PDF: https://arxiv.org/pdf/2602.21138v1 Original Link: http://arxiv.org/abs/2602.21138v1