no code implementations • 6 May 2024 • Vaidehi Srinivas, Avrim Blum
In this setting, an algorithm is given an instance of a problem, and a prediction of the solution.
no code implementations • 17 Jul 2023 • Quanquan C. Liu, Vaidehi Srinivas
Using this, we are able to interpolate between the offline and fully dynamic settings; when the $\ell_1$ error of the prediction is linear in the number of updates, we achieve the offline runtime of the algorithm (up to $\mathrm{poly} \log n$ factors).
no code implementations • 21 Apr 2022 • Vaidehi Srinivas, David P. Woodruff, Ziyu Xu, Samson Zhou
We initiate the study of the learning with expert advice problem in the streaming setting, and show lower and upper bounds.
