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Electronic Colloquium on Computational Complexity

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REPORTS > AUTHORS > ORI SBERLO:
All reports by Author Ori Sberlo:

TR22-008 | 14th January 2022
Gil Cohen, Dean Doron, Ori Sberlo

Approximating Large Powers of Stochastic Matrices in Small Space

We give a deterministic space-efficient algorithm for approximating powers of stochastic matrices. On input a $w \times w$ stochastic matrix $A$, our algorithm approximates $A^{n}$ in space $\widetilde{O}(\log n + \sqrt{\log n}\cdot \log w)$ to within high accuracy. This improves upon the seminal work by Saks and Zhou (FOCS'95), that ... more >>>


TR21-020 | 15th February 2021
Gil Cohen, Dean Doron, Oren Renard, Ori Sberlo, Amnon Ta-Shma

Error Reduction For Weighted PRGs Against Read Once Branching Programs

Weighted pseudorandom generators (WPRGs), introduced by Braverman, Cohen and Garg [BCG20], is a generalization of pseudorandom generators (PRGs) in which arbitrary real weights are considered rather than a probability mass. Braverman et al. constructed WPRGs against read once branching programs (ROBPs) with near-optimal dependence on the error parameter. Chattopadhyay and ... more >>>




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