834 research outputs found
Probabilistic Spectral Sparsification In Sublinear Time
In this paper, we introduce a variant of spectral sparsification, called
probabilistic -spectral sparsification. Roughly speaking,
it preserves the cut value of any cut with an
multiplicative error and a additive error. We show how
to produce a probabilistic -spectral sparsifier with
edges in time
time for unweighted undirected graph. This gives fastest known sub-linear time
algorithms for different cut problems on unweighted undirected graph such as
- An time -approximation
algorithm for the sparsest cut problem and the balanced separator problem.
- A time approximation minimum s-t cut algorithm
with an additive error
Minimum Cuts in Near-Linear Time
We significantly improve known time bounds for solving the minimum cut
problem on undirected graphs. We use a ``semi-duality'' between minimum cuts
and maximum spanning tree packings combined with our previously developed
random sampling techniques. We give a randomized algorithm that finds a minimum
cut in an m-edge, n-vertex graph with high probability in O(m log^3 n) time. We
also give a simpler randomized algorithm that finds all minimum cuts with high
probability in O(n^2 log n) time. This variant has an optimal RNC
parallelization. Both variants improve on the previous best time bound of O(n^2
log^3 n). Other applications of the tree-packing approach are new, nearly tight
bounds on the number of near minimum cuts a graph may have and a new data
structure for representing them in a space-efficient manner
Odd Paths, Cycles and -joins: Connections and Algorithms
Minimizing the weight of an edge set satisfying parity constraints is a
challenging branch of combinatorial optimization as witnessed by the binary
hypergraph chapter of Alexander Schrijver's book ``Combinatorial Optimization''
(Chapter 80). This area contains relevant graph theory problems including open
cases of the Max Cut problem, or some multiflow problems. We clarify the
interconnections of some problems and establish three levels of difficulties.
On the one hand, we prove that the Shortest Odd Path problem in an undirected
graph without cycles of negative total weight and several related problems are
NP-hard, settling a long-standing open question asked by Lov\'asz (Open Problem
27 in Schrijver's book ``Combinatorial Optimization''. On the other hand, we
provide a polynomial-time algorithm to the closely related and well-studied
Minimum-weight Odd -Join problem for non-negative weights, whose
complexity, however, was not known; more generally, we solve the Minimum-weight
Odd -Join problem in FPT time when parameterized by . If negative
weights are also allowed, then finding a minimum-weight odd -join is
equivalent to the Minimum-weight Odd -Join problem for arbitrary weights,
whose complexity is only conjectured to be polynomially solvable. The analogous
problems for digraphs are also considered.Comment: 24 pages, 2 figure
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