Ashkan Soleymani, Gabriele Farina · 2026 · arXiv (Cornell University)
DOI: 10.48550/arxiv.2610.30122 · cited by 0 works (OpenAlex) · open-access PDF
ونحن نعطي ألغازًا لتحديد نقطة ثابتة تقريبًا من $\eps$ من أي نموذج $d$ لا يتناسق مع نموذج $\ell_\infty$ في الوقت $\log(1/\eps)^O{O(\log^2 d)}$. في عمقها ، يستخدم طريقةنا أداة زيادة لتقليل منطقة البحث جغرافيًا.
Machine translation (Meta M2M100); the English original follows.
We give an algorithm for computing an $\eps$-approximate fixed point of any $d$-dimensional nonexpansion with respect to the $\ell_\infty$ norm in time $\log(1/\eps)^{O(\log^2 d)}$. At its core, our method uses a boosting argument to geometrically shrink a search region. Among other consequences, our algorithm implies that simple stochastic games can be solved in quasipolynomial time.
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Topics: Algorithm, Mathematics, Boosting (machine learning), Simple (philosophy), Norm (philosophy), Point (geometry)
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