 We also obtain an adversarially robust algorithm for the L_2-heavy hitters problem using%DIFDELCMD < \mathcal{O}\left(%%% \frac{\log n{\epsilon^2}}%DIFDELCMD < \right) %%% bits of space. Our bounds are optimal up to \text{poly(\log\log n+\log(1/\epsilon)) factors, and improve the 1{\epsilon^3} dependence of }  Ben-Eliezer et  al.
<meaning-changed>  We also obtain an adversarially robust algorithm for the L_2-heavy hitters problem using%DIFDELCMD < \mathcal{O}\left(%%% \frac{\log n{\epsilon^2}}%DIFDELCMD < \right) %%% bits of space. Our bounds are optimal up to \text{poly(\log\log n+\log(1/\epsilon)) factors, and improve the 1{\epsilon^3} dependence of }  Ben-Eliezer et  al.
 We also obtain an adversarially robust algorithm for the L_2-heavy hitters problem using%DIFDELCMD < \mathcal{O}\left(%%% \frac{\log n{\epsilon^2}}%DIFDELCMD < \right) %%% (\log\log n+\log(1/\epsilon)) factors, and improve the 1{\epsilon^3} dependence of } Ben-Eliezer et al.