7,993 research outputs found
Constant Factor Approximation for Balanced Cut in the PIE model
We propose and study a new semi-random semi-adversarial model for Balanced
Cut, a planted model with permutation-invariant random edges (PIE). Our model
is much more general than planted models considered previously. Consider a set
of vertices V partitioned into two clusters and of equal size. Let
be an arbitrary graph on with no edges between and . Let
be a set of edges sampled from an arbitrary permutation-invariant
distribution (a distribution that is invariant under permutation of vertices in
and in ). Then we say that is a graph with
permutation-invariant random edges.
We present an approximation algorithm for the Balanced Cut problem that finds
a balanced cut of cost in this model.
In the regime when , this is a
constant factor approximation with respect to the cost of the planted cut.Comment: Full version of the paper at the 46th ACM Symposium on the Theory of
Computing (STOC 2014). 32 page
Sparse Signal Processing Concepts for Efficient 5G System Design
As it becomes increasingly apparent that 4G will not be able to meet the
emerging demands of future mobile communication systems, the question what
could make up a 5G system, what are the crucial challenges and what are the key
drivers is part of intensive, ongoing discussions. Partly due to the advent of
compressive sensing, methods that can optimally exploit sparsity in signals
have received tremendous attention in recent years. In this paper we will
describe a variety of scenarios in which signal sparsity arises naturally in 5G
wireless systems. Signal sparsity and the associated rich collection of tools
and algorithms will thus be a viable source for innovation in 5G wireless
system design. We will discribe applications of this sparse signal processing
paradigm in MIMO random access, cloud radio access networks, compressive
channel-source network coding, and embedded security. We will also emphasize
important open problem that may arise in 5G system design, for which sparsity
will potentially play a key role in their solution.Comment: 18 pages, 5 figures, accepted for publication in IEEE Acces
Evolutionary algorithm-based analysis of gravitational microlensing lightcurves
A new algorithm developed to perform autonomous fitting of gravitational
microlensing lightcurves is presented. The new algorithm is conceptually
simple, versatile and robust, and parallelises trivially; it combines features
of extant evolutionary algorithms with some novel ones, and fares well on the
problem of fitting binary-lens microlensing lightcurves, as well as on a number
of other difficult optimisation problems. Success rates in excess of 90% are
achieved when fitting synthetic though noisy binary-lens lightcurves, allowing
no more than 20 minutes per fit on a desktop computer; this success rate is
shown to compare very favourably with that of both a conventional (iterated
simplex) algorithm, and a more state-of-the-art, artificial neural
network-based approach. As such, this work provides proof of concept for the
use of an evolutionary algorithm as the basis for real-time, autonomous
modelling of microlensing events. Further work is required to investigate how
the algorithm will fare when faced with more complex and realistic microlensing
modelling problems; it is, however, argued here that the use of parallel
computing platforms, such as inexpensive graphics processing units, should
allow fitting times to be constrained to under an hour, even when dealing with
complicated microlensing models. In any event, it is hoped that this work might
stimulate some interest in evolutionary algorithms, and that the algorithm
described here might prove useful for solving microlensing and/or more general
model-fitting problems.Comment: 14 pages, 3 figures; accepted for publication in MNRA
Efficient One-Way Secret-Key Agreement and Private Channel Coding via Polarization
We introduce explicit schemes based on the polarization phenomenon for the
tasks of one-way secret key agreement from common randomness and private
channel coding. For the former task, we show how to use common randomness and
insecure one-way communication to obtain a strongly secure key such that the
key construction has a complexity essentially linear in the blocklength and the
rate at which the key is produced is optimal, i.e., equal to the one-way
secret-key rate. For the latter task, we present a private channel coding
scheme that achieves the secrecy capacity using the condition of strong secrecy
and whose encoding and decoding complexity are again essentially linear in the
blocklength.Comment: 18.1 pages, 2 figures, 2 table
Engineering a static verification tool for GPU kernels
We report on practical experiences over the last 2.5 years related to the engineering of GPUVerify, a static verification tool for OpenCL and CUDA GPU kernels, plotting the progress of GPUVerify from a prototype to a fully functional and relatively efficient analysis tool. Our hope is that this experience report will serve the verification community by helping to inform future tooling efforts. © 2014 Springer International Publishing
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