33,568 research outputs found
Succinct Partial Sums and Fenwick Trees
We consider the well-studied partial sums problem in succint space where one
is to maintain an array of n k-bit integers subject to updates such that
partial sums queries can be efficiently answered. We present two succint
versions of the Fenwick Tree - which is known for its simplicity and
practicality. Our results hold in the encoding model where one is allowed to
reuse the space from the input data. Our main result is the first that only
requires nk + o(n) bits of space while still supporting sum/update in O(log_b
n) / O(b log_b n) time where 2 <= b <= log^O(1) n. The second result shows how
optimal time for sum/update can be achieved while only slightly increasing the
space usage to nk + o(nk) bits. Beyond Fenwick Trees, the results are primarily
based on bit-packing and sampling - making them very practical - and they also
allow for simple optimal parallelization
A bandwidth theorem for approximate decompositions
We provide a degree condition on a regular -vertex graph which ensures
the existence of a near optimal packing of any family of bounded
degree -vertex -chromatic separable graphs into . In general, this
degree condition is best possible.
Here a graph is separable if it has a sublinear separator whose removal
results in a set of components of sublinear size. Equivalently, the
separability condition can be replaced by that of having small bandwidth. Thus
our result can be viewed as a version of the bandwidth theorem of B\"ottcher,
Schacht and Taraz in the setting of approximate decompositions.
More precisely, let be the infimum over all
ensuring an approximate -decomposition of any sufficiently large regular
-vertex graph of degree at least . Now suppose that is an
-vertex graph which is close to -regular for some and suppose that is a sequence of bounded
degree -vertex -chromatic separable graphs with . We show that there is an edge-disjoint packing of
into .
If the are bipartite, then is sufficient. In
particular, this yields an approximate version of the tree packing conjecture
in the setting of regular host graphs of high degree. Similarly, our result
implies approximate versions of the Oberwolfach problem, the Alspach problem
and the existence of resolvable designs in the setting of regular host graphs
of high degree.Comment: Final version, to appear in the Proceedings of the London
Mathematical Societ
Analysis of the Min-Sum Algorithm for Packing and Covering Problems via Linear Programming
Message-passing algorithms based on belief-propagation (BP) are successfully
used in many applications including decoding error correcting codes and solving
constraint satisfaction and inference problems. BP-based algorithms operate
over graph representations, called factor graphs, that are used to model the
input. Although in many cases BP-based algorithms exhibit impressive empirical
results, not much has been proved when the factor graphs have cycles.
This work deals with packing and covering integer programs in which the
constraint matrix is zero-one, the constraint vector is integral, and the
variables are subject to box constraints. We study the performance of the
min-sum algorithm when applied to the corresponding factor graph models of
packing and covering LPs.
We compare the solutions computed by the min-sum algorithm for packing and
covering problems to the optimal solutions of the corresponding linear
programming (LP) relaxations. In particular, we prove that if the LP has an
optimal fractional solution, then for each fractional component, the min-sum
algorithm either computes multiple solutions or the solution oscillates below
and above the fraction. This implies that the min-sum algorithm computes the
optimal integral solution only if the LP has a unique optimal solution that is
integral.
The converse is not true in general. For a special case of packing and
covering problems, we prove that if the LP has a unique optimal solution that
is integral and on the boundary of the box constraints, then the min-sum
algorithm computes the optimal solution in pseudo-polynomial time.
Our results unify and extend recent results for the maximum weight matching
problem by [Sanghavi et al.,'2011] and [Bayati et al., 2011] and for the
maximum weight independent set problem [Sanghavi et al.'2009]
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