Under the auspices of the Computational Complexity Foundation (CCF)

REPORTS > KEYWORD > DISTRIBUTION-FREE LEARNING:
Reports tagged with Distribution-free learning:
TR23-006 | 20th January 2023
Koch, Strassle, and Tan [SODA 2023], show that, under the randomized exponential time hypothesis, there is no distribution-free PAC-learning algorithm that runs in time $n^{\tilde O(\log\log s)}$ for the classes of $n$-variable size-$s$ DNF, size-$s$ Decision Tree, and $\log s$-Junta by DNF (that returns a DNF hypothesis). Assuming a natural ... more >>>