JMLR<p>&#39;Compressed and distributed least-squares regression: convergence rates with applications to federated learning&#39;, by Constantin Philippenko, Aymeric Dieuleveut.</p><p><a href="http://jmlr.org/papers/v25/23-1040.html" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">http://</span><span class="ellipsis">jmlr.org/papers/v25/23-1040.ht</span><span class="invisible">ml</span></a> <br /> <br /><a href="https://sigmoid.social/tags/stochastic" class="mention hashtag" rel="tag">#<span>stochastic</span></a> <a href="https://sigmoid.social/tags/randomizing" class="mention hashtag" rel="tag">#<span>randomizing</span></a> <a href="https://sigmoid.social/tags/compression" class="mention hashtag" rel="tag">#<span>compression</span></a></p>