Daniel Kane, Shachar Lovett, Shay Moran

We construct near optimal linear decision trees for a variety of decision problems in combinatorics and discrete geometry.

For example, for any constant $k$, we construct linear decision trees that solve the $k$-SUM problem on $n$ elements using $O(n \log^2 n)$ linear queries.

Moreover, the queries we use are comparison ...
more >>>

Gal Arnon, Tomer Grossman

We introduce the notion of \emph{Min-Entropic Optimality} thereby providing a framework for arguing that a given algorithm computes a function better than any other algorithm. An algorithm is $k(n)$ Min-Entropic Optimal if for every distribution $D$ with min-entropy at least $k(n)$, its expected running time when its input is drawn ... more >>>