no code implementations • 24 Feb 2016 • Anindya De, Michael Saks, Sijian Tang
We show that for $\mu > 0$, the sample complexity (and hence the algorithmic complexity) is bounded by a polynomial in $k$, $n$ and $1/\varepsilon$ improving upon the previous best result of $\mathsf{poly}(k^{\log\log k}, n, 1/\varepsilon)$ due to Lovett and Zhang.
no code implementations • 6 Feb 2013 • Ankur Moitra, Michael Saks
This improves on algorithm of Wigderson and Yehudayoff that runs in quasi-polynomial time for any $\mu > 0$ and the polynomial time algorithm of Dvir et al which was shown to work for $\mu \gtrapprox 0. 30$ by Batman et al.
