1 code implementation • NeurIPS 2019 • Su Jia, Viswanath Nagarajan, Fatemeh Navidi, R. Ravi
Our new approximation algorithms provide guarantees that are nearly best-possible and work for the general case of a large number of noisy outcomes per test or per hypothesis where the performance degrades smoothly with this number.
no code implementations • 5 Jun 2016 • Fatemeh Navidi, Prabhanjan Kambadur, Viswanath Nagarajan
We obtain a logarithmic factor approximation algorithm for this adaptive ranking problem, which is the best possible (unless P=NP).