Georgia Institute of Technology College of Sciences

In the talk we will consider the problem of deciding whether agiven $r$-uniform hypergraph $H$ with minimum vertex degree atleast $c|V(H)|$, has a vertex 2-coloring. This problem has beenknown also as the Property B of a hypergraph. Motivated by an oldresult of Edwards for graphs, we summarize what can be deducedfrom his method about the complexity of the problem for densehypergraphs. We obtain the optimal dichotomy results for2-colorings of $r$-uniform hypergraphs when $r=3,4,$ and 5. During the talk we will present the NP-completeness results followed bypolynomial time algorithms for the problems above the thresholdvalue. The coloring algorithms rely on the known Tur\'{a}n numbersfor graphs and hypergraphs and the hypergraph removal lemma.

In 1997 Kannan and Frieze defined the \emph{cut-norm} $\left\Vert A\right\Vert_{\square}$ of a $p\times q$ matrix $A=\left[ a_{ij}\right] $ as%\[\left\Vert A\right\Vert _{\square}=\frac{1}{pq}\max\left\{ \left\vert\sum_{i\in X}\sum_{j\in Y}a_{ij}\right\vert :X\subset\left[ p\right],Y\subset\left[ q\right] ,\text{ }X,Y\neq\varnothing\right\} .\]More recently, Lov\'{a}sz and his collaborators used the norm $\left\VertA\right\Vert _{\square}$ to define a useful measure of similarity between anytwo graphs, which they called \emph{cut-distance. }It turns out that the cut-distance can be extended to arbitrary complexmatrices, even non-square ones. This talk will introduce the basics of thecut-norm and \ cut-distance for arbitrary matrices, and present relationsbetween these functions and some fundamental matricial norms, like theoperator norm. In particular, these relations give a solution to a problem of Lov\'{a}sz.Similar questions are discussed about the related norm\[\left\Vert A\right\Vert _{\boxdot}=\max\left\{ \frac{1}{\sqrt{\left\vertX\right\vert \left\vert Y\right\vert }}\left\vert \sum_{i\in X}\sum_{j\inY}a_{ij}\right\vert :X\subset\left[ p\right] ,Y\subset\left[ q\right],\text{ }X,Y\neq\varnothing\right\} .\]which plays a central role in the \textquotedblleft expander mixinglemma\textquotedblright.

Abstract: A hitting set for a collection of sets T is a set that has a non-empty intersection with eachset in T; the hitting set problem is to find a hitting set of minimum cardinality. Motivated bythe fact that there are instances of the hitting set problem where the number of subsets to behit is large, we introduce the notion of implicit hitting set problems. In an implicit hitting setproblem the collection of sets to be hit is typically too large to list explicitly; instead, an oracleis provided which, given a set H, either determines that H is a hitting set or returns a set inT that H does not hit. I will show a number of examples of classic implicit hitting set problems,and give a generic algorithm for solving such problems exactly in an online model.I will also show how this framework is valuable in developing approximation algorithms by presenting a simple on-line algorithm for the minimum feedback vertex set problem. In particular, our algorithm gives an approximation factor of 1+ 2 log(np)/(np) for the random graph G_{n,p}.Joint work with Richard Karp, Erick Moreno-Centeno (UC, Berkeley) and Santosh Vempala (Georgia Tech).