11,680 research outputs found
Approximating the Held-Karp Bound for Metric TSP in Nearly Linear Time
We give a nearly linear time randomized approximation scheme for the
Held-Karp bound [Held and Karp, 1970] for metric TSP. Formally, given an
undirected edge-weighted graph on edges and , the
algorithm outputs in time, with high probability, a
-approximation to the Held-Karp bound on the metric TSP instance
induced by the shortest path metric on . The algorithm can also be used to
output a corresponding solution to the Subtour Elimination LP. We substantially
improve upon the running time achieved previously
by Garg and Khandekar. The LP solution can be used to obtain a fast randomized
-approximation for metric TSP which improves
upon the running time of previous implementations of Christofides' algorithm
Precoder Design for Physical Layer Multicasting
This paper studies the instantaneous rate maximization and the weighted sum
delay minimization problems over a K-user multicast channel, where multiple
antennas are available at the transmitter as well as at all the receivers.
Motivated by the degree of freedom optimality and the simplicity offered by
linear precoding schemes, we consider the design of linear precoders using the
aforementioned two criteria. We first consider the scenario wherein the linear
precoder can be any complex-valued matrix subject to rank and power
constraints. We propose cyclic alternating ascent based precoder design
algorithms and establish their convergence to respective stationary points.
Simulation results reveal that our proposed algorithms considerably outperform
known competing solutions. We then consider a scenario in which the linear
precoder can be formed by selecting and concatenating precoders from a given
finite codebook of precoding matrices, subject to rank and power constraints.
We show that under this scenario, the instantaneous rate maximization problem
is equivalent to a robust submodular maximization problem which is strongly NP
hard. We propose a deterministic approximation algorithm and show that it
yields a bicriteria approximation. For the weighted sum delay minimization
problem we propose a simple deterministic greedy algorithm, which at each step
entails approximately maximizing a submodular set function subject to multiple
knapsack constraints, and establish its performance guarantee.Comment: 37 pages, 8 figures, submitted to IEEE Trans. Signal Pro
Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions
We analyze a class of estimators based on convex relaxation for solving
high-dimensional matrix decomposition problems. The observations are noisy
realizations of a linear transformation of the sum of an
approximately) low rank matrix with a second matrix
endowed with a complementary form of low-dimensional structure;
this set-up includes many statistical models of interest, including factor
analysis, multi-task regression, and robust covariance estimation. We derive a
general theorem that bounds the Frobenius norm error for an estimate of the
pair obtained by solving a convex optimization
problem that combines the nuclear norm with a general decomposable regularizer.
Our results utilize a "spikiness" condition that is related to but milder than
singular vector incoherence. We specialize our general result to two cases that
have been studied in past work: low rank plus an entrywise sparse matrix, and
low rank plus a columnwise sparse matrix. For both models, our theory yields
non-asymptotic Frobenius error bounds for both deterministic and stochastic
noise matrices, and applies to matrices that can be exactly or
approximately low rank, and matrices that can be exactly or
approximately sparse. Moreover, for the case of stochastic noise matrices and
the identity observation operator, we establish matching lower bounds on the
minimax error. The sharpness of our predictions is confirmed by numerical
simulations.Comment: 41 pages, 2 figure
Dagstuhl Reports : Volume 1, Issue 2, February 2011
Online Privacy: Towards Informational Self-Determination on the Internet (Dagstuhl Perspectives Workshop 11061) : Simone Fischer-Hübner, Chris Hoofnagle, Kai Rannenberg, Michael Waidner, Ioannis Krontiris and Michael Marhöfer Self-Repairing Programs (Dagstuhl Seminar 11062) : Mauro Pezzé, Martin C. Rinard, Westley Weimer and Andreas Zeller Theory and Applications of Graph Searching Problems (Dagstuhl Seminar 11071) : Fedor V. Fomin, Pierre Fraigniaud, Stephan Kreutzer and Dimitrios M. Thilikos Combinatorial and Algorithmic Aspects of Sequence Processing (Dagstuhl Seminar 11081) : Maxime Crochemore, Lila Kari, Mehryar Mohri and Dirk Nowotka Packing and Scheduling Algorithms for Information and Communication Services (Dagstuhl Seminar 11091) Klaus Jansen, Claire Mathieu, Hadas Shachnai and Neal E. Youn
Efficient Reactive Brownian Dynamics
We develop a Split Reactive Brownian Dynamics (SRBD) algorithm for particle
simulations of reaction-diffusion systems based on the Doi or volume reactivity
model, in which pairs of particles react with a specified Poisson rate if they
are closer than a chosen reactive distance. In our Doi model, we ensure that
the microscopic reaction rules for various association and disassociation
reactions are consistent with detailed balance (time reversibility) at
thermodynamic equilibrium. The SRBD algorithm uses Strang splitting in time to
separate reaction and diffusion, and solves both the diffusion-only and
reaction-only subproblems exactly, even at high packing densities. To
efficiently process reactions without uncontrolled approximations, SRBD employs
an event-driven algorithm that processes reactions in a time-ordered sequence
over the duration of the time step. A grid of cells with size larger than all
of the reactive distances is used to schedule and process the reactions, but
unlike traditional grid-based methods such as Reaction-Diffusion Master
Equation (RDME) algorithms, the results of SRBD are statistically independent
of the size of the grid used to accelerate the processing of reactions. We use
the SRBD algorithm to compute the effective macroscopic reaction rate for both
reaction- and diffusion-limited irreversible association in three dimensions.
We also study long-time tails in the time correlation functions for reversible
association at thermodynamic equilibrium. Finally, we compare different
particle and continuum methods on a model exhibiting a Turing-like instability
and pattern formation. We find that for models in which particles diffuse off
lattice, such as the Doi model, reactions lead to a spurious enhancement of the
effective diffusion coefficients.Comment: To appear in J. Chem. Phy
- …