  In the Edge Bipartization problem one is given an undirected graph $G$ and an
integer $k$, and the question is whether $k$ edges can be deleted from $G$ so
that it becomes bipartite. In 2006, Guo et al. [J. Comput. Syst. Sci.,
72(8):1386-1396, 2006] proposed an algorithm solving this problem in time
$O(2^k m^2)$; today, this algorithm is a textbook example of an application of
the iterative compression technique. Despite extensive progress in the
understanding of the parameterized complexity of graph separation problems in
the recent years, no significant improvement upon this result has been yet
reported.
  We present an algorithm for Edge Bipartization that works in time $O(1.977^k
nm)$, which is the first algorithm with the running time dependence on the
parameter better than $2^k$. To this end, we combine the general iterative
compression strategy of Guo et al. [J. Comput. Syst. Sci., 72(8):1386-1396,
2006], the technique proposed by Wahlstrom [SODA 2014, 1762-1781] of using a
polynomial-time solvable relaxation in the form of a Valued Constraint
Satisfaction Problem to guide a bounded-depth branching algorithm, and an
involved Measure & Conquer analysis of the recursion tree.
