Beating $(1-1/e)$-Approximation for Weighted Stochastic Matching

In the stochastic weighted matching problem, the goal is to find a large-weight matching of a graph when we are uncertain about the existence of its edges. In particular, each edge $e$ has a known weight $we$ but is realized independently with some probability $pe$. The algorithm may query an edge to see whether it is realized. We consider the well-studied query commit version of the problem, in which any queried edge that happens to be realized must be included in the solution. Gamlath, Kale, and Svensson showed that when the input graph is bipartite, the problem admits a $(1-1/e)$-approximation. In this paper, we give an algorithm that for an absolute constant $\delta > 0.0014$ obtains a $(1-1/e+\delta)$-approximation, therefore breaking this prevalent bound.