  We give the first constant-factor approximation algorithm for Sparsest Cut
with general demands in bounded treewidth graphs. In contrast to previous
algorithms, which rely on the flow-cut gap and/or metric embeddings, our
approach exploits the Sherali-Adams hierarchy of linear programming
relaxations.
