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0905.2479
|
A note on a complex Hilbert metric with application to domain of
analyticity for entropy rate of hidden Markov processes
|
math.DS cs.IT math.IT
|
In this note, we show that small complex perturbations of positive matrices
are contractions, with respect to a complex version of the Hilbert metric, on
the standard complex simplex. We show that this metric can be used to obtain
estimates of the domain of analyticity of entropy rate for a hidden Markov
process when the underlying Markov chain has strictly positive transition
probabilities.
|
0905.2501
|
Macrodynamics of users' behavior in Information Retrieval
|
cs.IR
|
We present a method to geometrize massive data sets from search engines query
logs. For this purpose, a macrodynamic-like quantitative model of the
Information Retrieval (IR) process is developed, whose paradigm is inspired by
basic constructions of Einstein's general relativity theory in which all IR
objects are uniformly placed in a common Room. The Room has a structure similar
to Einsteinian spacetime, namely that of a smooth manifold. Documents and
queries are treated as matter objects and sources of material fields.
Relevance, the central notion of IR, becomes a dynamical issue controlled by
both gravitation (or, more precisely, as the motion in a curved spacetime) and
forces originating from the interactions of matter fields. The spatio-temporal
description ascribes dynamics to any document or query, thus providing a
uniform description for documents of both initially static and dynamical
nature. Within the IR context, the techniques presented are based on two ideas.
The first is the placement of all objects participating in IR into a common
continuous space. The second idea is the `objectivization' of the IR process;
instead of expressing users' wishes, we consider the overall IR as an objective
physical process, representing the IR process in terms of motion in a given
external-fields configuration. Various semantic environments are treated as
various IR universes.
|
0905.2635
|
Point-Set Registration: Coherent Point Drift
|
cs.CV
|
Point set registration is a key component in many computer vision tasks. The
goal of point set registration is to assign correspondences between two sets of
points and to recover the transformation that maps one point set to the other.
Multiple factors, including an unknown non-rigid spatial transformation, large
dimensionality of point set, noise and outliers, make the point set
registration a challenging problem. We introduce a probabilistic method, called
the Coherent Point Drift (CPD) algorithm, for both rigid and non-rigid point
set registration. We consider the alignment of two point sets as a probability
density estimation problem. We fit the GMM centroids (representing the first
point set) to the data (the second point set) by maximizing the likelihood. We
force the GMM centroids to move coherently as a group to preserve the
topological structure of the point sets. In the rigid case, we impose the
coherence constraint by re-parametrization of GMM centroid locations with rigid
parameters and derive a closed form solution of the maximization step of the EM
algorithm in arbitrary dimensions. In the non-rigid case, we impose the
coherence constraint by regularizing the displacement field and using the
variational calculus to derive the optimal transformation. We also introduce a
fast algorithm that reduces the method computation complexity to linear. We
test the CPD algorithm for both rigid and non-rigid transformations in the
presence of noise, outliers and missing points, where CPD shows accurate
results and outperforms current state-of-the-art methods.
|
0905.2638
|
Secure Degrees of Freedom for Gaussian Channels with Interference:
Structured Codes Outperform Gaussian Signaling
|
cs.IT math.IT
|
In this work, we prove that a positive secure degree of freedom is achievable
for a large class of Gaussian channels as long as the channel is not degraded
and the channel is fully connected. This class includes the MAC wire-tap
channel, the 2-user interference channel with confidential messages, the 2-user
interference channel with an external eavesdropper. Best known achievable
schemes to date for these channels use Gaussian signaling. In this work, we
show that structured codes outperform Gaussian random codes at high SNR when
channel gains are real numbers.
|
0905.2639
|
Information-theoretic limits of selecting binary graphical models in
high dimensions
|
cs.IT cs.LG math.IT math.ST stat.TH
|
The problem of graphical model selection is to correctly estimate the graph
structure of a Markov random field given samples from the underlying
distribution. We analyze the information-theoretic limitations of the problem
of graph selection for binary Markov random fields under high-dimensional
scaling, in which the graph size $p$ and the number of edges $k$, and/or the
maximal node degree $d$ are allowed to increase to infinity as a function of
the sample size $n$. For pairwise binary Markov random fields, we derive both
necessary and sufficient conditions for correct graph selection over the class
$\mathcal{G}_{p,k}$ of graphs on $p$ vertices with at most $k$ edges, and over
the class $\mathcal{G}_{p,d}$ of graphs on $p$ vertices with maximum degree at
most $d$. For the class $\mathcal{G}_{p, k}$, we establish the existence of
constants $c$ and $c'$ such that if $\numobs < c k \log p$, any method has
error probability at least 1/2 uniformly over the family, and we demonstrate a
graph decoder that succeeds with high probability uniformly over the family for
sample sizes $\numobs > c' k^2 \log p$. Similarly, for the class
$\mathcal{G}_{p,d}$, we exhibit constants $c$ and $c'$ such that for $n < c d^2
\log p$, any method fails with probability at least 1/2, and we demonstrate a
graph decoder that succeeds with high probability for $n > c' d^3 \log p$.
|
0905.2640
|
The Gaussian Many-to-One Interference Channel with Confidential Messages
|
cs.IT math.IT
|
We investigate the $K$-user many-to-one interference channel with
confidential messages in which the $K$th user experiences interference from all
other $K-1$ users, and is at the same time treated as an eavesdropper to all
the messages of these users. We derive achievable rates and an upper bound on
the sum rate for this channel and show that the gap between the achievable sum
rate and its upper bound is $\log_2(K-1)$ bits per channel use under very
strong interference, when the interfering users have equal power constraints
and interfering link channel gains. The main contributions of this work are:
(i) nested lattice codes are shown to provide secrecy when interference is
present, (ii) a secrecy sum rate upper bound is found for strong interference
regime and (iii) it is proved that under very strong interference and a
symmetric setting, the gap between the achievable sum rate and the upper bound
is constant with respect to transmission powers.
|
0905.2643
|
K-user Interference Channels: Achievable Secrecy Rate and Degrees of
Freedom
|
cs.IT math.IT
|
In this work, we consider achievable secrecy rates for symmetric $K$-user ($K
\ge 3$) interference channels with confidential messages. We find that nested
lattice codes and layered coding are useful in providing secrecy for these
channels. Achievable secrecy rates are derived for very strong interference. In
addition, we derive the secure degrees of freedom for a range of channel
parameters. As a by-product of our approach, we also demonstrate that nested
lattice codes are useful for K-user symmetric interference channels without
secrecy constraints in that they yield higher degrees of freedom than previous
results.
|
0905.2645
|
Providing Secrecy with Lattice Codes
|
cs.IT math.IT
|
Recent results have shown that lattice codes can be used to construct good
channel codes, source codes and physical layer network codes for Gaussian
channels. On the other hand, for Gaussian channels with secrecy constraints,
efforts to date rely on random codes. In this work, we provide a tool to bridge
these two areas so that the secrecy rate can be computed when lattice codes are
used. In particular, we address the problem of bounding equivocation rates
under nonlinear modulus operation that is present in lattice encoders/decoders.
The technique is then demonstrated in two Gaussian channel examples: (1) a
Gaussian wiretap channel with a cooperative jammer, and (2) a multi-hop line
network from a source to a destination with untrusted intermediate relay nodes
from whom the information needs to be kept secret. In both cases, lattice codes
are used to facilitate cooperative jamming. In the second case, interestingly,
we demonstrate that a non-vanishing positive secrecy rate is achievable
regardless of the number of hops.
|
0905.2649
|
An Immune System Inspired Approach to Automated Program Verification
|
cs.NE
|
An immune system inspired Artificial Immune System (AIS) algorithm is
presented, and is used for the purposes of automated program verification.
Relevant immunological concepts are discussed and the field of AIS is briefly
reviewed. It is proposed to use this AIS algorithm for a specific automated
program verification task: that of predicting shape of program invariants. It
is shown that the algorithm correctly predicts program invariant shape for a
variety of benchmarked programs.
|
0905.2657
|
Web 2.0 OLAP: From Data Cubes to Tag Clouds
|
cs.DB
|
Increasingly, business projects are ephemeral. New Business Intelligence
tools must support ad-lib data sources and quick perusal. Meanwhile, tag clouds
are a popular community-driven visualization technique. Hence, we investigate
tag-cloud views with support for OLAP operations such as roll-ups, slices,
dices, clustering, and drill-downs. As a case study, we implemented an
application where users can upload data and immediately navigate through its ad
hoc dimensions. To support social networking, views can be easily shared and
embedded in other Web sites. Algorithmically, our tag-cloud views are
approximate range top-k queries over spontaneous data cubes. We present
experimental evidence that iceberg cuboids provide adequate online
approximations. We benchmark several browser-oblivious tag-cloud layout
optimizations.
|
0905.2659
|
Coalitional Games for Distributed Collaborative Spectrum Sensing in
Cognitive Radio Networks
|
cs.GT cs.IT math.IT
|
Collaborative spectrum sensing among secondary users (SUs) in cognitive
networks is shown to yield a significant performance improvement. However,
there exists an inherent trade off between the gains in terms of probability of
detection of the primary user (PU) and the costs in terms of false alarm
probability. In this paper, we study the impact of this trade off on the
topology and the dynamics of a network of SUs seeking to reduce the
interference on the PU through collaborative sensing. Moreover, while existing
literature mainly focused on centralized solutions for collaborative sensing,
we propose distributed collaboration strategies through game theory. We model
the problem as a non-transferable coalitional game, and propose a distributed
algorithm for coalition formation through simple merge and split rules. Through
the proposed algorithm, SUs can autonomously collaborate and self-organize into
disjoint independent coalitions, while maximizing their detection probability
taking into account the cooperation costs (in terms of false alarm). We study
the stability of the resulting network structure, and show that a maximum
number of SUs per formed coalition exists for the proposed utility model.
Simulation results show that the proposed algorithm allows a reduction of up to
86.6% of the average missing probability per SU (probability of missing the
detection of the PU) relative to the non-cooperative case, while maintaining a
certain false alarm level. In addition, through simulations, we compare the
performance of the proposed distributed solution with respect to an optimal
centralized solution that minimizes the average missing probability per SU.
Finally, the results also show how the proposed algorithm autonomously adapts
the network topology to environmental changes such as mobility.
|
0905.2676
|
On the Benefits of Bandwidth Limiting in Decentralized Vector Multiple
Access Channels
|
cs.IT math.IT
|
We study the network spectral efficiency of decentralized vector multiple
access channels (MACs) when the number of accessible dimensions per transmitter
is strategically limited. Considering each dimension as a frequency band, we
call this limiting process bandwidth limiting (BL). Assuming that each
transmitter maximizes its own data rate by water-filling over the available
frequency bands, we consider two scenarios. In the first scenario, transmitters
use non-intersecting sets of bands (spectral resource partition), and in the
second one, they freely exploit all the available frequency bands (spectral
resource sharing). In the latter case, successive interference cancelation
(SIC) is used. We show the existence of an optimal number of dimensions that a
transmitter must use in order to maximize the network performance measured in
terms of spectral efficiency. We provide a closed form expression for the
optimal number of accessible bands in the first scenario. Such an optimum
point, depends on the number of active transmitters, the number of available
frequency bands and the different signal-to-noise ratios. In the second
scenario, we show that BL does not bring a significant improvement on the
network spectral efficiency, when all transmitters use the same BL policy. For
both scenarios, we provide simulation results to validate our conclusions.
|
0905.2718
|
Achievable Rate and Optimal Physical Layer Rate Allocation in
Interference-Free Wireless Networks
|
cs.IT math.IT
|
We analyze the achievable rate in interference-free wireless networks with
physical layer fading channels and orthogonal multiple access. As a starting
point, the point-to-point channel is considered. We find the optimal physical
and network layer rate trade-off which maximizes the achievable overall rate
for both a fixed rate transmission scheme and an improved scheme based on
multiple virtual users and superposition coding. These initial results are
extended to the network setting, where, based on a cut-set formulation, the
achievable rate at each node and its upper bound are derived. We propose a
distributed optimization algorithm which allows to jointly determine the
maximum achievable rate, the optimal physical layer rates on each network link,
and an opportunistic back-pressure-type routing strategy on the network layer.
This inherently justifies the layered architecture in existing wireless
networks. Finally, we show that the proposed layered optimization approach can
achieve almost all of the ergodic network capacity in high SNR.
|
0905.2796
|
Sparse Network Coding with Overlapping Classes
|
cs.IT math.IT
|
This paper presents a novel approach to network coding for distribution of
large files. Instead of the usual approach of splitting packets into disjoint
classes (also known as generations) we propose the use of overlapping classes.
The overlapping allows the decoder to alternate between Gaussian elimination
and back substitution, simultaneously boosting the performance and reducing the
decoding complexity. Our approach can be seen as a combination of fountain
coding and network coding. Simulation results are presented that demonstrate
the promise of our approach.
|
0905.2817
|
Cavity approach to the Sourlas code system
|
cond-mat.dis-nn cond-mat.stat-mech cs.IT math.IT
|
The statistical physics properties of regular and irregular Sourlas codes are
investigated in this paper by the cavity method. At finite temperatures, the
free energy density of these coding systems is derived and compared with the
result obtained by the replica method. In the zero temperature limit, the
Shannon's bound is recovered in the case of infinite-body interactions while
the code rate is still finite. However, the decoding performance as obtained by
the replica theory has not considered the zero-temperature entropic effect. The
cavity approach is able to consider the ground-state entropy. It leads to a set
of evanescent cavity fields propagation equations which further improve the
decoding performance, as confirmed by our numerical simulations on single
instances. For the irregular Sourlas code, we find that it takes the trade-off
between good dynamical property and high performance of decoding. In agreement
with the results found from the algorithmic point of view, the decoding
exhibits a first order phase transition as occurs in the regular code system
with three-body interactions. The cavity approach for the Sourlas code system
can be extended to consider first-step replica-symmetry-breaking.
|
0905.2882
|
Do not Choose Representation just Change: An Experimental Study in
States based EA
|
cs.NE cs.AI
|
Our aim in this paper is to analyse the phenotypic effects (evolvability) of
diverse coding conversion operators in an instance of the states based
evolutionary algorithm (SEA). Since the representation of solutions or the
selection of the best encoding during the optimization process has been proved
to be very important for the efficiency of evolutionary algorithms (EAs), we
will discuss a strategy of coupling more than one representation and different
procedures of conversion from one coding to another during the search.
Elsewhere, some EAs try to use multiple representations (SM-GA, SEA, etc.) in
intention to benefit from the characteristics of each of them. In spite of
those results, this paper shows that the change of the representation is also a
crucial approach to take into consideration while attempting to increase the
performances of such EAs. As a demonstrative example, we use a two states SEA
(2-SEA) which has two identical search spaces but different coding conversion
operators. The results show that the way of changing from one coding to another
and not only the choice of the best representation nor the representation
itself is very advantageous and must be taken into account in order to
well-desing and improve EAs execution.
|
0905.2919
|
Succinct Representation of Codes with Applications to Testing
|
cs.IT math.IT
|
Motivated by questions in property testing, we search for linear
error-correcting codes that have the "single local orbit" property: i.e., they
are specified by a single local constraint and its translations under the
symmetry group of the code. We show that the dual of every "sparse" binary code
whose coordinates are indexed by elements of F_{2^n} for prime n, and whose
symmetry group includes the group of non-singular affine transformations of
F_{2^n} has the single local orbit property. (A code is said to be "sparse" if
it contains polynomially many codewords in its block length.) In particular
this class includes the dual-BCH codes for whose duals (i.e., for BCH codes)
simple bases were not known. Our result gives the first short (O(n)-bit, as
opposed to the natural exp(n)-bit) description of a low-weight basis for BCH
codes. The interest in the "single local orbit" property comes from the recent
result of Kaufman and Sudan (STOC 2008) that shows that the duals of codes that
have the single local orbit property under the affine symmetry group are
locally testable. When combined with our main result, this shows that all
sparse affine-invariant codes over the coordinates F_{2^n} for prime n are
locally testable. If, in addition to n being prime, if 2^n-1 is also prime
(i.e., 2^n-1 is a Mersenne prime), then we get that every sparse cyclic code
also has the single local orbit. In particular this implies that BCH codes of
Mersenne prime length are generated by a single low-weight codeword and its
cyclic shifts.
|
0905.2924
|
Colorization of Natural Images via L1 Optimization
|
cs.CV
|
Natural images in the colour space YUV have been observed to have a
non-Gaussian, heavy tailed distribution (called 'sparse') when the filter
G(U)(r) = U(r) - sum_{s \in N(r)} w{(Y)_{rs}} U(s), is applied to the
chromacity channel U (and equivalently to V), where w is a weighting function
constructed from the intensity component Y [1]. In this paper we develop
Bayesian analysis of the colorization problem using the filter response as a
regularization term to arrive at a non-convex optimization problem. This
problem is convexified using L1 optimization which often gives the same results
for sparse signals [2]. It is observed that L1 optimization, in many cases,
over-performs the famous colorization algorithm by Levin et al [3].
|
0905.2958
|
A statistical learning approach to color demosaicing
|
cs.CV
|
A statistical learning/inference framework for color demosaicing is
presented. We start with simplistic assumptions about color constancy, and
recast color demosaicing as a blind linear inverse problem: color parameterizes
the unknown kernel, while brightness takes on the role of a latent variable. An
expectation-maximization algorithm naturally suggests itself for the estimation
of them both. Then, as we gradually broaden the family of hypothesis where
color is learned, we let our demosaicing behave adaptively, in a manner that
reflects our prior knowledge about the statistics of color images. We show that
we can incorporate realistic, learned priors without essentially changing the
complexity of the simple expectation-maximization algorithm we started with.
|
0905.2990
|
Automatic Summarization System coupled with a Question-Answering System
(QAAS)
|
cs.IR cs.CL
|
To select the most relevant sentences of a document, it uses an optimal
decision algorithm that combines several metrics. The metrics processes,
weighting and extract pertinence sentences by statistical and informational
algorithms. This technique might improve a Question-Answering system, whose
function is to provide an exact answer to a question in natural language. In
this paper, we present the results obtained by coupling the Cortex summarizer
with a Question-Answering system (QAAS). Two configurations have been
evaluated. In the first one, a low compression level is selected and the
summarization system is only used as a noise filter. In the second
configuration, the system actually functions as a summarizer, with a very high
level of compression. Our results on French corpus demonstrate that the
coupling of Automatic Summarization system with a Question-Answering system is
promising. Then the system has been adapted to generate a customized summary
depending on the specific question. Tests on a french multi-document corpus
have been realized, and the personalized QAAS system obtains the best
performances.
|
0905.2997
|
Average-Case Active Learning with Costs
|
cs.LG
|
We analyze the expected cost of a greedy active learning algorithm. Our
analysis extends previous work to a more general setting in which different
queries have different costs. Moreover, queries may have more than two possible
responses and the distribution over hypotheses may be non uniform. Specific
applications include active learning with label costs, active learning for
multiclass and partial label queries, and batch mode active learning. We also
discuss an approximate version of interest when there are very many queries.
|
0905.3023
|
Interference and Deployment Issues for Cognitive Radio Systems in
Shadowing Environments
|
cs.IT math.IT
|
In this paper we describe a model for calculating the aggregate interference
encountered by primary receivers in the presence of randomly placed cognitive
radios (CRs). We show that incorporating the impact of distance attenuation and
lognormal fading on each constituent interferer in the aggregate, leads to a
composite interference that cannot be satisfactorily modeled by a lognormal.
Using the interference statistics we determine a number of key parameters
needed for the deployment of CRs. Examples of these are the exclusion zone
radius, needed to protect the primary receiver under different types of fading
environments and acceptable interference levels, and the numbers of CRs that
can be deployed. We further show that if the CRs have apriori knowledge of the
radio environment map (REM), then a much larger number of CRs can be deployed
especially in a high density environment. Given REM information, we also look
at the CR numbers achieved by two different types of techniques to process the
scheduling information.
|
0905.3030
|
Performance of Cognitive Radio Systems with Imperfect Radio Environment
Map Information
|
cs.IT math.IT
|
In this paper we describe the effect of imperfections in the radio
environment map (REM) information on the performance of cognitive radio (CR)
systems. Via simulations we explore the relationship between the required
precision of the REM and various channel/system properties. For example, the
degree of spatial correlation in the shadow fading is a key factor as is the
interference constraint employed by the primary user. Based on the CR
interferers obtained from the simulations, we characterize the temporal
behavior of such systems by computing the level crossing rates (LCRs) of the
cumulative interference represented by these CRs. This evaluates the effect of
short term fluctuations above acceptable interference levels due to the fast
fading. We derive analytical formulae for the LCRs in Rayleigh and Rician fast
fading conditions. The analytical results are verified by Monte Carlo
simulations.
|
0905.3076
|
On a Class of Doubly-Generalized LDPC Codes with Single Parity-Check
Variable Nodes
|
cs.IT math.IT
|
A class of doubly-generalized low-density parity-check (D-GLDPC) codes, where
single parity-check (SPC) codes are used as variable nodes (VNs), is
investigated. An expression for the growth rate of the weight distribution of
any D-GLDPC ensemble with a uniform check node (CN) set is presented at first,
together with an analytical technique for its efficient evaluation. These tools
are then used for detailed analysis of a case study, namely, a rate-1/2 D-GLDPC
ensemble where all the CNs are (7,4) Hamming codes and all the VNs are length-7
SPC codes. It is illustrated how the VN representations can heavily affect the
code properties and how different VN representations can be combined within the
same graph to enhance some of the code parameters. The analysis is conducted
over the binary erasure channel. Interesting features of the new codes include
the capability of achieving a good compromise between waterfall and error floor
performance while preserving graphical regularity, and values of threshold
outperforming LDPC counterparts.
|
0905.3086
|
Deterministic Relay Networks with State Information
|
cs.IT math.IT
|
Motivated by fading channels and erasure channels, the problem of reliable
communication over deterministic relay networks is studied, in which relay
nodes receive a function of the incoming signals and a random network state. An
achievable rate is characterized for the case in which destination nodes have
full knowledge of the state information. If the relay nodes receive a linear
function of the incoming signals and the state in a finite field, then the
achievable rate is shown to be optimal, meeting the cut-set upper bound on the
capacity. This result generalizes on a unified framework the work of
Avestimehr, Diggavi, and Tse on the deterministic networks with state
dependency, the work of Dana, Gowaikar, Palanki, Hassibi, and Effros on linear
erasure networks with interference, and the work of Smith and Vishwanath on
linear erasure networks with broadcast.
|
0905.3108
|
A Note on the Complexity of the Satisfiability Problem for Graded Modal
Logics
|
cs.LO cs.AI cs.CC
|
Graded modal logic is the formal language obtained from ordinary
(propositional) modal logic by endowing its modal operators with cardinality
constraints. Under the familiar possible-worlds semantics, these augmented
modal operators receive interpretations such as "It is true at no fewer than 15
accessible worlds that...", or "It is true at no more than 2 accessible worlds
that...". We investigate the complexity of satisfiability for this language
over some familiar classes of frames. This problem is more challenging than its
ordinary modal logic counterpart--especially in the case of transitive frames,
where graded modal logic lacks the tree-model property. We obtain tight
complexity bounds for the problem of determining the satisfiability of a given
graded modal logic formula over the classes of frames characterized by any
combination of reflexivity, seriality, symmetry, transitivity and the Euclidean
property.
|
0905.3109
|
Interference Channels with Source Cooperation
|
cs.IT math.IT
|
The role of cooperation in managing interference - a fundamental feature of
the wireless channel - is investigated by studying the two-user Gaussian
interference channel where the source nodes can both transmit and receive in
full-duplex. The sum-capacity of this channel is obtained within a gap of a
constant number of bits. The coding scheme used builds up on the superposition
scheme of Han and Kobayashi (1981) for the two-user interference channel
without cooperation. New upperbounds on the sum-capacity are also derived. The
same coding scheme is shown to obtain the sum-capacity of the symmetric
two-user Gaussian interference channel with noiseless feedback within a
constant gap.
|
0905.3135
|
The discrete logarithm problem in the group of non-singular circulant
matrices
|
cs.CR cs.DM cs.IT math.IT
|
The discrete logarithm problem is one of the backbones in public key
cryptography. In this paper we study the discrete logarithm problem in the
group of circulant matrices over a finite field. This gives rise to secure and
fast public key cryptosystems.
|
0905.3178
|
SQS-graphs of Solov'eva-Phelps codes
|
math.CO cs.IT math.IT
|
A binary extended 1-perfect code $\mathcal C$ folds over its kernel via the
Steiner quadruple systems associated with its codewords. The resulting folding,
proposed as a graph invariant for $\mathcal C$, distinguishes among the 361
nonlinear codes $\mathcal C$ of kernel dimension $\kappa$ obtained via
Solov'eva-Phelps doubling construction, where $9\geq\kappa\geq 5$. Each of the
361 resulting graphs has most of its nonloop edges expressible in terms of
lexicographically ordered quarters of products of classes from extended
1-perfect partitions of length 8 (as classified by Phelps) and loops mostly
expressible in terms of the lines of the Fano plane.
|
0905.3201
|
On the Statistics of Cognitive Radio Capacity in Shadowing and Fast
Fading Environments
|
cs.IT math.IT
|
In this paper we consider the capacity of the cognitive radio channel in a
fading environment under a "low interference regime". This capacity depends
critically on a power loss parameter, $\alpha$, which governs how much transmit
power the cognitive radio dedicates to relaying the primary message. We derive
a simple, accurate approximation to $\alpha$ which gives considerable insight
into system capacity. We also investigate the effects of system parameters and
propagation environment on $\alpha$ and the cognitive radio capacity. In all
cases, the use of the approximation is shown to be extremely accurate. Finally,
we derive the probability that the "low interference regime" holds and
demonstrate that this is the dominant case, especially in practical cognitive
radio deployment scenarios.
|
0905.3245
|
Novel Algorithm for Sparse Solutions to Linear Inverse Problems with
Multiple Measurements
|
cs.IT math.IT
|
In this report, a novel efficient algorithm for recovery of jointly sparse
signals (sparse matrix) from multiple incomplete measurements has been
presented, in particular, the NESTA-based MMV optimization method. In a
nutshell, the jointly sparse recovery is obviously superior to applying
standard sparse reconstruction methods to each channel individually. Moreover
several efforts have been made to improve the NESTA-based MMV algorithm, in
particular, (1) the NESTA-based MMV algorithm for partially known support to
greatly improve the convergence rate, (2) the detection of partial (or all)
locations of unknown jointly sparse signals by using so-called MUSIC algorithm;
(3) the iterative NESTA-based algorithm by combing hard thresholding technique
to decrease the numbers of measurements. It has been shown that by using
proposed approach one can recover the unknown sparse matrix X with () Spark A
-sparsity from () Spark A measurements, predicted in Ref. [1], where the
measurement matrix denoted by A satisfies the so-called restricted isometry
property (RIP). Under a very mild condition on the sparsity of X and
characteristics of the A, the iterative hard threshold (IHT)-based MMV method
has been shown to be also a very good candidate.
|
0905.3318
|
An Object-Oriented and Fast Lexicon for Semantic Generation
|
cs.CL cs.DB cs.DS cs.IR cs.PL
|
This paper is about the technical design of a large computational lexicon,
its storage, and its access from a Prolog environment. Traditionally, efficient
access and storage of data structures is implemented by a relational database
management system. In Delilah, a lexicon-based NLP system, efficient access to
the lexicon by the semantic generator is vital. We show that our highly
detailed HPSG-style lexical specifications do not fit well in the Relational
Model, and that they cannot be efficiently retrieved. We argue that they fit
more naturally in the Object-Oriented Model. Although storage of objects is
redundant, we claim that efficient access is still possible by applying
indexing, and compression techniques from the Relational Model to the
Object-Oriented Model. We demonstrate that it is possible to implement
object-oriented storage and fast access in ISO Prolog.
|
0905.3347
|
Information Distance in Multiples
|
cs.CV cs.LG
|
Information distance is a parameter-free similarity measure based on
compression, used in pattern recognition, data mining, phylogeny, clustering,
and classification. The notion of information distance is extended from pairs
to multiples (finite lists). We study maximal overlap, metricity, universality,
minimal overlap, additivity, and normalized information distance in multiples.
We use the theoretical notion of Kolmogorov complexity which for practical
purposes is approximated by the length of the compressed version of the file
involved, using a real-world compression program.
{\em Index Terms}-- Information distance, multiples, pattern recognition,
data mining, similarity, Kolmogorov complexity
|
0905.3356
|
Memento Ludi: Information Retrieval from a Game-Theoretic Perspective
|
cs.IR cs.GT
|
We develop a macro-model of information retrieval process using Game Theory
as a mathematical theory of conflicts. We represent the participants of the
Information Retrieval process as a game of two abstract players. The first
player is the `intellectual crowd' of users of search engines, the second is a
community of information retrieval systems. In order to apply Game Theory, we
treat search log data as Nash equilibrium strategies and solve the inverse
problem of finding appropriate payoff functions. For that, we suggest a
particular model, which we call Alpha model. Within this model, we suggest a
method, called shifting, which makes it possible to partially control the
behavior of massive users.
This Note is addressed to researchers in both game theory (providing a new
class of real life problems) and information retrieval, for whom we present new
techniques to control the IR environment.
|
0905.3360
|
A Generalized Statistical Complexity Measure: Applications to Quantum
Systems
|
quant-ph cs.IT math.IT nlin.AO physics.atom-ph
|
A two-parameter family of complexity measures $\tilde{C}^{(\alpha,\beta)}$
based on the R\'enyi entropies is introduced and characterized by a detailed
study of its mathematical properties. This family is the generalization of a
continuous version of the LMC complexity, which is recovered for $\alpha=1$ and
$\beta=2$. These complexity measures are obtained by multiplying two quantities
bringing global information on the probability distribution defining the
system. When one of the parameters, $\alpha$ or $\beta$, goes to infinity, one
of the global factors becomes a local factor. For this special case, the
complexity is calculated on different quantum systems: H-atom, harmonic
oscillator and square well.
|
0905.3369
|
Learning Nonlinear Dynamic Models
|
cs.AI cs.LG
|
We present a novel approach for learning nonlinear dynamic models, which
leads to a new set of tools capable of solving problems that are otherwise
difficult. We provide theory showing this new approach is consistent for models
with long range structure, and apply the approach to motion capture and
high-dimensional video data, yielding results superior to standard
alternatives.
|
0905.3378
|
Interpretations of the Web of Data
|
cs.AI cs.DL
|
The emerging Web of Data utilizes the web infrastructure to represent and
interrelate data. The foundational standards of the Web of Data include the
Uniform Resource Identifier (URI) and the Resource Description Framework (RDF).
URIs are used to identify resources and RDF is used to relate resources. While
RDF has been posited as a logic language designed specifically for knowledge
representation and reasoning, it is more generally useful if it can
conveniently support other models of computing. In order to realize the Web of
Data as a general-purpose medium for storing and processing the world's data,
it is necessary to separate RDF from its logic language legacy and frame it
simply as a data model. Moreover, there is significant advantage in seeing the
Semantic Web as a particular interpretation of the Web of Data that is focused
specifically on knowledge representation and reasoning. By doing so, other
interpretations of the Web of Data are exposed that realize RDF in different
capacities and in support of different computing models.
|
0905.3407
|
Throughput and Delay Scaling in Supportive Two-Tier Networks
|
cs.IT math.IT
|
Consider a wireless network that has two tiers with different priorities: a
primary tier vs. a secondary tier, which is an emerging network scenario with
the advancement of cognitive radio technologies. The primary tier consists of
randomly distributed legacy nodes of density $n$, which have an absolute
priority to access the spectrum. The secondary tier consists of randomly
distributed cognitive nodes of density $m=n^\beta$ with $\beta\geq 2$, which
can only access the spectrum opportunistically to limit the interference to the
primary tier. Based on the assumption that the secondary tier is allowed to
route the packets for the primary tier, we investigate the throughput and delay
scaling laws of the two tiers in the following two scenarios: i) the primary
and secondary nodes are all static; ii) the primary nodes are static while the
secondary nodes are mobile. With the proposed protocols for the two tiers, we
show that the primary tier can achieve a per-node throughput scaling of
$\lambda_p(n)=\Theta(1/\log n)$ in the above two scenarios. In the associated
delay analysis for the first scenario, we show that the primary tier can
achieve a delay scaling of $D_p(n)=\Theta(\sqrt{n^\beta\log n}\lambda_p(n))$
with $\lambda_p(n)=O(1/\log n)$. In the second scenario, with two mobility
models considered for the secondary nodes: an i.i.d. mobility model and a
random walk model, we show that the primary tier can achieve delay scaling laws
of $\Theta(1)$ and $\Theta(1/S)$, respectively, where $S$ is the random walk
step size. The throughput and delay scaling laws for the secondary tier are
also established, which are the same as those for a stand-alone network.
|
0905.3428
|
Finding Anomalous Periodic Time Series: An Application to Catalogs of
Periodic Variable Stars
|
cs.LG astro-ph.IM physics.data-an
|
Catalogs of periodic variable stars contain large numbers of periodic
light-curves (photometric time series data from the astrophysics domain).
Separating anomalous objects from well-known classes is an important step
towards the discovery of new classes of astronomical objects. Most anomaly
detection methods for time series data assume either a single continuous time
series or a set of time series whose periods are aligned. Light-curve data
precludes the use of these methods as the periods of any given pair of
light-curves may be out of sync. One may use an existing anomaly detection
method if, prior to similarity calculation, one performs the costly act of
aligning two light-curves, an operation that scales poorly to massive data
sets. This paper presents PCAD, an unsupervised anomaly detection method for
large sets of unsynchronized periodic time-series data, that outputs a ranked
list of both global and local anomalies. It calculates its anomaly score for
each light-curve in relation to a set of centroids produced by a modified
k-means clustering algorithm. Our method is able to scale to large data sets
through the use of sampling. We validate our method on both light-curve data
and other time series data sets. We demonstrate its effectiveness at finding
known anomalies, and discuss the effect of sample size and number of centroids
on our results. We compare our method to naive solutions and existing time
series anomaly detection methods for unphased data, and show that PCAD's
reported anomalies are comparable to or better than all other methods. Finally,
astrophysicists on our team have verified that PCAD finds true anomalies that
might be indicative of novel astrophysical phenomena.
|
0905.3434
|
Exploiting Opportunistic Multiuser Detection in Decentralized Multiuser
MIMO Systems
|
cs.IT math.IT
|
This paper studies the design of a decentralized multiuser multi-antenna
(MIMO) system for spectrum sharing over a fixed narrow band, where the
coexisting users independently update their transmit covariance matrices for
individual transmit-rate maximization via an iterative manner. This design
problem was usually investigated in the literature by assuming that each user
treats the co-channel interference from all the other users as additional
(colored) noise at the receiver, i.e., the conventional single-user decoder
(SUD) is applied. This paper proposes a new decoding method for the
decentralized multiuser MIMO system, whereby each user opportunistically
cancels the co-channel interference from some or all of the other users via
applying multiuser detection techniques, thus termed opportunistic multiuser
detection (OMD). This paper studies the optimal transmit covariance design for
users' iterative maximization of individual transmit rates with the proposed
OMD, and demonstrates the resulting capacity gains in decentralized multiuser
MIMO systems against the conventional SUD.
|
0905.3436
|
On Active Learning and Supervised Transmission of Spectrum Sharing Based
Cognitive Radios by Exploiting Hidden Primary Radio Feedback
|
cs.IT math.IT
|
This paper studies the wireless spectrum sharing between a pair of
distributed primary radio (PR) and cognitive radio (CR) links. Assuming that
the PR link adapts its transmit power and/or rate upon receiving an
interference signal from the CR and such transmit adaptations are observable by
the CR, this results in a new form of feedback from the PR to CR, refereed to
as hidden PR feedback, whereby the CR learns the PR's strategy for transmit
adaptations without the need of a dedicated feedback channel from the PR. In
this paper, we exploit the hidden PR feedback to design new learning and
transmission schemes for spectrum sharing based CRs, namely active learning and
supervised transmission. For active learning, the CR initiatively sends a
probing signal to interfere with the PR, and from the observed PR transmit
adaptations the CR estimates the channel gain from its transmitter to the PR
receiver, which is essential for the CR to control its interference to the PR
during the subsequent data transmission. This paper proposes a new transmission
protocol for the CR to implement the active learning and the solutions to deal
with various practical issues for implementation, such as time synchronization,
rate estimation granularity, power measurement noise, and channel variation.
Furthermore, with the acquired knowledge from active learning, the CR designs a
supervised data transmission by effectively controlling the interference powers
both to and from the PR, so as to achieve the optimum performance tradeoffs for
the PR and CR links. Numerical results are provided to evaluate the
effectiveness of the proposed schemes for CRs under different system setups.
|
0905.3527
|
Quantum Annealing for Clustering
|
cond-mat.dis-nn cond-mat.stat-mech cs.LG quant-ph
|
This paper studies quantum annealing (QA) for clustering, which can be seen
as an extension of simulated annealing (SA). We derive a QA algorithm for
clustering and propose an annealing schedule, which is crucial in practice.
Experiments show the proposed QA algorithm finds better clustering assignments
than SA. Furthermore, QA is as easy as SA to implement.
|
0905.3528
|
Quantum Annealing for Variational Bayes Inference
|
cond-mat.dis-nn cond-mat.stat-mech cs.LG quant-ph
|
This paper presents studies on a deterministic annealing algorithm based on
quantum annealing for variational Bayes (QAVB) inference, which can be seen as
an extension of the simulated annealing for variational Bayes (SAVB) inference.
QAVB is as easy as SAVB to implement. Experiments revealed QAVB finds a better
local optimum than SAVB in terms of the variational free energy in latent
Dirichlet allocation (LDA).
|
0905.3582
|
Profiling of a network behind an infectious disease outbreak
|
cs.AI q-bio.PE
|
Stochasticity and spatial heterogeneity are of great interest recently in
studying the spread of an infectious disease. The presented method solves an
inverse problem to discover the effectively decisive topology of a
heterogeneous network and reveal the transmission parameters which govern the
stochastic spreads over the network from a dataset on an infectious disease
outbreak in the early growth phase. Populations in a combination of
epidemiological compartment models and a meta-population network model are
described by stochastic differential equations. Probability density functions
are derived from the equations and used for the maximal likelihood estimation
of the topology and parameters. The method is tested with computationally
synthesized datasets and the WHO dataset on SARS outbreak.
|
0905.3587
|
Prediction, Retrodiction, and The Amount of Information Stored in the
Present
|
cond-mat.stat-mech cond-mat.dis-nn cs.IT math.IT physics.data-an
|
We introduce an ambidextrous view of stochastic dynamical systems, comparing
their forward-time and reverse-time representations and then integrating them
into a single time-symmetric representation. The perspective is useful
theoretically, computationally, and conceptually. Mathematically, we prove that
the excess entropy--a familiar measure of organization in complex systems--is
the mutual information not only between the past and future, but also between
the predictive and retrodictive causal states. Practically, we exploit the
connection between prediction and retrodiction to directly calculate the excess
entropy. Conceptually, these lead one to discover new system invariants for
stochastic dynamical systems: crypticity (information accessibility) and causal
irreversibility. Ultimately, we introduce a time-symmetric representation that
unifies all these quantities, compressing the two directional representations
into one. The resulting compression offers a new conception of the amount of
information stored in the present.
|
0905.3602
|
Level Crossing Rates of Interference in Cognitive Radio Networks
|
cs.IT math.IT
|
The future deployment of cognitive radios is critically dependent on the fact
that the incumbent primary user system must remain as oblivious as possible to
their presence. This in turn heavily relies on the fluctuations of the
interfering cognitive radio signals. In this letter we compute the level
crossing rates of the cumulative interference created by the cognitive radios.
We derive analytical formulae for the level crossing rates in Rayleigh and
Rician fast fading conditions. We approximate Rayleigh and Rician level
crossing rates using fluctuation rates of gamma and scaled noncentral $\chi^2$
processes respectively. The analytical results and the approximations used in
their derivations are verified by Monte Carlo simulations and the analysis is
applied to a particular CR allocation strategy.
|
0905.3640
|
Coevolutionary Genetic Algorithms for Establishing Nash Equilibrium in
Symmetric Cournot Games
|
cs.GT cs.LG
|
We use co-evolutionary genetic algorithms to model the players' learning
process in several Cournot models, and evaluate them in terms of their
convergence to the Nash Equilibrium. The "social-learning" versions of the two
co-evolutionary algorithms we introduce, establish Nash Equilibrium in those
models, in contrast to the "individual learning" versions which, as we see
here, do not imply the convergence of the players' strategies to the Nash
outcome. When players use "canonical co-evolutionary genetic algorithms" as
learning algorithms, the process of the game is an ergodic Markov Chain, and
therefore we analyze simulation results using both the relevant methodology and
more general statistical tests, to find that in the "social" case, states
leading to NE play are highly frequent at the stationary distribution of the
chain, in contrast to the "individual learning" case, when NE is not reached at
all in our simulations; to find that the expected Hamming distance of the
states at the limiting distribution from the "NE state" is significantly
smaller in the "social" than in the "individual learning case"; to estimate the
expected time that the "social" algorithms need to get to the "NE state" and
verify their robustness and finally to show that a large fraction of the games
played are indeed at the Nash Equilibrium.
|
0905.3689
|
Optimized Training and Feedback for MIMO Downlink Channels
|
cs.IT math.IT
|
We consider a MIMO fading broadcast channel where channel state information
is acquired at user terminals via downlink training and channel feedback is
used to provide transmitter channel state information (CSIT) to the base
station. The feedback channel (the corresponding uplink) is modeled as an AWGN
channel, orthogonal across users. The total bandwidth consumed is the sum of
the bandwidth/resources used for downlink training, channel feedback, and data
transmission. Assuming that the channel follows a block fading model and that
zeroforcing beamforming is used, we optimize the net achievable rate for
unquantized (analog) and quantized (digital) channel feedback. The optimal
number of downlink training pilots is seen to be essentially the same for both
feedback techniques, but digital feedback is shown to provide a larger net rate
than analog feedback.
|
0905.3720
|
Where are the really hard manipulation problems? The phase transition in
manipulating the veto rule
|
cs.AI cs.CC
|
Voting is a simple mechanism to aggregate the preferences of agents. Many
voting rules have been shown to be NP-hard to manipulate. However, a number of
recent theoretical results suggest that this complexity may only be in the
worst-case since manipulation is often easy in practice. In this paper, we show
that empirical studies are useful in improving our understanding of this issue.
We demonstrate that there is a smooth transition in the probability that a
coalition can elect a desired candidate using the veto rule as the size of the
manipulating coalition increases. We show that a rescaled probability curve
displays a simple and universal form independent of the size of the problem. We
argue that manipulation of the veto rule is asymptotically easy for many
independent and identically distributed votes even when the coalition of
manipulators is critical in size. Based on this argument, we identify a
situation in which manipulation is computationally hard. This is when votes are
highly correlated and the election is "hung". We show, however, that even a
single uncorrelated voter is enough to make manipulation easy again.
|
0905.3733
|
Trapping Set Enumerators for Repeat Multiple Accumulate Code Ensembles
|
cs.IT math.IT
|
The serial concatenation of a repetition code with two or more accumulators
has the advantage of a simple encoder structure. Furthermore, the resulting
ensemble is asymptotically good and exhibits minimum distance growing linearly
with block length. However, in practice these codes cannot be decoded by a
maximum likelihood decoder, and iterative decoding schemes must be employed.
For low-density parity-check codes, the notion of trapping sets has been
introduced to estimate the performance of these codes under iterative message
passing decoding. In this paper, we present a closed form finite length
ensemble trapping set enumerator for repeat multiple accumulate codes by
creating a trellis representation of trapping sets. We also obtain the
asymptotic expressions when the block length tends to infinity and evaluate
them numerically.
|
0905.3755
|
Decompositions of All Different, Global Cardinality and Related
Constraints
|
cs.AI
|
We show that some common and important global constraints like ALL-DIFFERENT
and GCC can be decomposed into simple arithmetic constraints on which we
achieve bound or range consistency, and in some cases even greater pruning.
These decompositions can be easily added to new solvers. They also provide
other constraints with access to the state of the propagator by sharing of
variables. Such sharing can be used to improve propagation between constraints.
We report experiments with our decomposition in a pseudo-Boolean solver.
|
0905.3757
|
Circuit Complexity and Decompositions of Global Constraints
|
cs.AI cs.CC
|
We show that tools from circuit complexity can be used to study
decompositions of global constraints. In particular, we study decompositions of
global constraints into conjunctive normal form with the property that unit
propagation on the decomposition enforces the same level of consistency as a
specialized propagation algorithm. We prove that a constraint propagator has a
a polynomial size decomposition if and only if it can be computed by a
polynomial size monotone Boolean circuit. Lower bounds on the size of monotone
Boolean circuits thus translate to lower bounds on the size of decompositions
of global constraints. For instance, we prove that there is no polynomial sized
decomposition of the domain consistency propagator for the ALLDIFFERENT
constraint.
|
0905.3763
|
Scenario-based Stochastic Constraint Programming
|
cs.AI
|
To model combinatorial decision problems involving uncertainty and
probability, we extend the stochastic constraint programming framework proposed
in [Walsh, 2002] along a number of important dimensions (e.g. to multiple
chance constraints and to a range of new objectives). We also provide a new
(but equivalent) semantics based on scenarios. Using this semantics, we can
compile stochastic constraint programs down into conventional (nonstochastic)
constraint programs. This allows us to exploit the full power of existing
constraint solvers. We have implemented this framework for decision making
under uncertainty in stochastic OPL, a language which is based on the OPL
constraint modelling language [Hentenryck et al., 1999]. To illustrate the
potential of this framework, we model a wide range of problems in areas as
diverse as finance, agriculture and production.
|
0905.3766
|
Reasoning about soft constraints and conditional preferences: complexity
results and approximation techniques
|
cs.AI
|
Many real life optimization problems contain both hard and soft constraints,
as well as qualitative conditional preferences. However, there is no single
formalism to specify all three kinds of information. We therefore propose a
framework, based on both CP-nets and soft constraints, that handles both hard
and soft constraints as well as conditional preferences efficiently and
uniformly. We study the complexity of testing the consistency of preference
statements, and show how soft constraints can faithfully approximate the
semantics of conditional preference statements whilst improving the
computational complexity
|
0905.3769
|
Multiset Ordering Constraints
|
cs.AI
|
We identify a new and important global (or non-binary) constraint. This
constraint ensures that the values taken by two vectors of variables, when
viewed as multisets, are ordered. This constraint is useful for a number of
different applications including breaking symmetry and fuzzy constraint
satisfaction. We propose and implement an efficient linear time algorithm for
enforcing generalised arc consistency on such a multiset ordering constraint.
Experimental results on several problem domains show considerable promise.
|
0905.3771
|
Memory Retrieved from Single Neurons
|
cs.NE q-bio.NC
|
The paper examines the problem of accessing a vector memory from a single
neuron in a Hebbian neural network. It begins with the review of the author's
earlier method, which is different from the Hopfield model in that it recruits
neighboring neurons by spreading activity, making it possible for single or
group of neurons to become associated with vector memories. Some open issues
associated with this approach are identified. It is suggested that fragments
that generate stored memories could be associated with single neurons through
local spreading activity.
|
0905.3830
|
Tag Clouds for Displaying Semantics: The Case of Filmscripts
|
cs.AI
|
We relate tag clouds to other forms of visualization, including planar or
reduced dimensionality mapping, and Kohonen self-organizing maps. Using a
modified tag cloud visualization, we incorporate other information into it,
including text sequence and most pertinent words. Our notion of word pertinence
goes beyond just word frequency and instead takes a word in a mathematical
sense as located at the average of all of its pairwise relationships. We
capture semantics through context, taken as all pairwise relationships. Our
domain of application is that of filmscript analysis. The analysis of
filmscripts, always important for cinema, is experiencing a major gain in
importance in the context of television. Our objective in this work is to
visualize the semantics of filmscript, and beyond filmscript any other
partially structured, time-ordered, sequence of text segments. In particular we
develop an innovative approach to plot characterization.
|
0905.3858
|
Multicasting in Large Wireless Networks: Bounds on the Minimum Energy
per Bit
|
cs.IT math.IT
|
We consider scaling laws for maximal energy efficiency of communicating a
message to all the nodes in a wireless network, as the number of nodes in the
network becomes large. Two cases of large wireless networks are studied --
dense random networks and constant density (extended) random networks. In
addition, we also study finite size regular networks in order to understand how
regularity in node placement affects energy consumption.
We first establish an information-theoretic lower bound on the minimum energy
per bit for multicasting in arbitrary wireless networks when the channel state
information is not available at the transmitters. Upper bounds are obtained by
constructing a simple flooding scheme that requires no information at the
receivers about the channel states or the locations and identities of the
nodes. The gap between the upper and lower bounds is only a constant factor for
dense random networks and regular networks, and differs by a poly-logarithmic
factor for extended random networks. Furthermore, we show that the proposed
upper and lower bounds for random networks hold almost surely in the node
locations as the number of nodes approaches infinity.
|
0905.3885
|
Swap Bribery
|
cs.GT cs.AI
|
In voting theory, bribery is a form of manipulative behavior in which an
external actor (the briber) offers to pay the voters to change their votes in
order to get her preferred candidate elected. We investigate a model of bribery
where the price of each vote depends on the amount of change that the voter is
asked to implement. Specifically, in our model the briber can change a voter's
preference list by paying for a sequence of swaps of consecutive candidates.
Each swap may have a different price; the price of a bribery is the sum of the
prices of all swaps that it involves. We prove complexity results for this
model, which we call swap bribery, for a broad class of election systems,
including variants of approval and k-approval, Borda, Copeland, and maximin.
|
0905.3934
|
Cooperative encoding for secrecy in interference channels
|
cs.IT math.IT
|
This paper investigates the fundamental performance limits of the two-user
interference channel in the presence of an external eavesdropper. In this
setting, we construct an inner bound, to the secrecy capacity region, based on
the idea of cooperative encoding in which the two users cooperatively design
their randomized codebooks and jointly optimize their channel prefixing
distributions. Our achievability scheme also utilizes message-splitting in
order to allow for partial decoding of the interference at the non-intended
receiver. Outer bounds are then derived and used to establish the optimality of
the proposed scheme in certain cases. In the Gaussian case, the previously
proposed cooperative jamming and noise-forwarding techniques are shown to be
special cases of our proposed approach. Overall, our results provide structural
insights on how the interference can be exploited to increase the secrecy
capacity of wireless networks.
|
0905.3964
|
A New Solution to the Relative Orientation Problem using only 3 Points
and the Vertical Direction
|
cs.CV
|
This paper presents a new method to recover the relative pose between two
images, using three points and the vertical direction information. The vertical
direction can be determined in two ways: 1- using direct physical measurement
like IMU (inertial measurement unit), 2- using vertical vanishing point. This
knowledge of the vertical direction solves 2 unknowns among the 3 parameters of
the relative rotation, so that only 3 homologous points are requested to
position a couple of images. Rewriting the coplanarity equations leads to a
simpler solution. The remaining unknowns resolution is performed by an
algebraic method using Grobner bases. The elements necessary to build a
specific algebraic solver are given in this paper, allowing for a real-time
implementation. The results on real and synthetic data show the efficiency of
this method.
|
0905.3967
|
Optimal byzantine resilient convergence in oblivious robot networks
|
cs.DC cs.RO
|
Given a set of robots with arbitrary initial location and no agreement on a
global coordinate system, convergence requires that all robots asymptotically
approach the exact same, but unknown beforehand, location. Robots are
oblivious-- they do not recall the past computations -- and are allowed to move
in a one-dimensional space. Additionally, robots cannot communicate directly,
instead they obtain system related information only via visual sensors. We draw
a connection between the convergence problem in robot networks, and the
distributed \emph{approximate agreement} problem (that requires correct
processes to decide, for some constant $\epsilon$, values distance $\epsilon$
apart and within the range of initial proposed values). Surprisingly, even
though specifications are similar, the convergence implementation in robot
networks requires specific assumptions about synchrony and Byzantine
resilience. In more details, we prove necessary and sufficient conditions for
the convergence of mobile robots despite a subset of them being Byzantine (i.e.
they can exhibit arbitrary behavior). Additionally, we propose a deterministic
convergence algorithm for robot networks and analyze its correctness and
complexity in various synchrony settings. The proposed algorithm tolerates f
Byzantine robots for (2f+1)-sized robot networks in fully synchronous networks,
(3f+1)-sized in semi-synchronous networks. These bounds are optimal for the
class of cautious algorithms, which guarantee that correct robots always move
inside the range of positions of the correct robots.
|
0905.4022
|
Transfer Learning Using Feature Selection
|
cs.LG
|
We present three related ways of using Transfer Learning to improve feature
selection. The three methods address different problems, and hence share
different kinds of information between tasks or feature classes, but all three
are based on the information theoretic Minimum Description Length (MDL)
principle and share the same underlying Bayesian interpretation. The first
method, MIC, applies when predictive models are to be built simultaneously for
multiple tasks (``simultaneous transfer'') that share the same set of features.
MIC allows each feature to be added to none, some, or all of the task models
and is most beneficial for selecting a small set of predictive features from a
large pool of features, as is common in genomic and biological datasets. Our
second method, TPC (Three Part Coding), uses a similar methodology for the case
when the features can be divided into feature classes. Our third method,
Transfer-TPC, addresses the ``sequential transfer'' problem in which the task
to which we want to transfer knowledge may not be known in advance and may have
different amounts of data than the other tasks. Transfer-TPC is most beneficial
when we want to transfer knowledge between tasks which have unequal amounts of
labeled data, for example the data for disambiguating the senses of different
verbs. We demonstrate the effectiveness of these approaches with experimental
results on real world data pertaining to genomics and to Word Sense
Disambiguation (WSD).
|
0905.4023
|
DMT Optimality of LR-Aided Linear Decoders for a General Class of
Channels, Lattice Designs, and System Models
|
cs.IT math.IT
|
The work identifies the first general, explicit, and non-random MIMO
encoder-decoder structures that guarantee optimality with respect to the
diversity-multiplexing tradeoff (DMT), without employing a computationally
expensive maximum-likelihood (ML) receiver. Specifically, the work establishes
the DMT optimality of a class of regularized lattice decoders, and more
importantly the DMT optimality of their lattice-reduction (LR)-aided linear
counterparts. The results hold for all channel statistics, for all channel
dimensions, and most interestingly, irrespective of the particular lattice-code
applied. As a special case, it is established that the LLL-based LR-aided
linear implementation of the MMSE-GDFE lattice decoder facilitates DMT optimal
decoding of any lattice code at a worst-case complexity that grows at most
linearly in the data rate. This represents a fundamental reduction in the
decoding complexity when compared to ML decoding whose complexity is generally
exponential in rate.
The results' generality lends them applicable to a plethora of pertinent
communication scenarios such as quasi-static MIMO, MIMO-OFDM, ISI,
cooperative-relaying, and MIMO-ARQ channels, in all of which the DMT optimality
of the LR-aided linear decoder is guaranteed. The adopted approach yields
insight, and motivates further study, into joint transceiver designs with an
improved SNR gap to ML decoding.
|
0905.4039
|
Normalized Web Distance and Word Similarity
|
cs.CL cs.IR
|
There is a great deal of work in cognitive psychology, linguistics, and
computer science, about using word (or phrase) frequencies in context in text
corpora to develop measures for word similarity or word association, going back
to at least the 1960s. The goal of this chapter is to introduce the
normalizedis a general way to tap the amorphous low-grade knowledge available
for free on the Internet, typed in by local users aiming at personal
gratification of diverse objectives, and yet globally achieving what is
effectively the largest semantic electronic database in the world. Moreover,
this database is available for all by using any search engine that can return
aggregate page-count estimates for a large range of search-queries. In the
paper introducing the NWD it was called `normalized Google distance (NGD),' but
since Google doesn't allow computer searches anymore, we opt for the more
neutral and descriptive NWD. web distance (NWD) method to determine similarity
between words and phrases. It
|
0905.4057
|
Coalitional Game Theory for Communication Networks: A Tutorial
|
cs.IT cs.GT math.IT
|
Game theoretical techniques have recently become prevalent in many
engineering applications, notably in communications. With the emergence of
cooperation as a new communication paradigm, and the need for self-organizing,
decentralized, and autonomic networks, it has become imperative to seek
suitable game theoretical tools that allow to analyze and study the behavior
and interactions of the nodes in future communication networks. In this
context, this tutorial introduces the concepts of cooperative game theory,
namely coalitional games, and their potential applications in communication and
wireless networks. For this purpose, we classify coalitional games into three
categories: Canonical coalitional games, coalition formation games, and
coalitional graph games. This new classification represents an
application-oriented approach for understanding and analyzing coalitional
games. For each class of coalitional games, we present the fundamental
components, introduce the key properties, mathematical techniques, and solution
concepts, and describe the methodologies for applying these games in several
applications drawn from the state-of-the-art research in communications. In a
nutshell, this article constitutes a unified treatment of coalitional game
theory tailored to the demands of communications and network engineers.
|
0905.4087
|
Structural Solutions for Cross-Layer Optimization of Wireless Multimedia
Transmission
|
cs.MM cs.IT math.IT
|
In this paper, we propose a systematic solution to the problem of cross-layer
optimization for delay-sensitive media transmission over time-varying wireless
channels as well as investigate the structures and properties of this solution,
such that it can be easily implemented in various multimedia systems and
applications. Specifically, we formulate this problem as a finite-horizon
Markov decision process (MDP) by explicitly considering the users'
heterogeneous multimedia traffic characteristics (e.g. delay deadlines,
distortion impacts and dependencies etc.), time-varying network conditions as
well as, importantly, their ability to adapt their cross-layer transmission
strategies in response to these dynamics. Based on the heterogeneous
characteristics of the media packets, we are able to express the transmission
priorities between packets as a new type of directed acyclic graph (DAG). This
DAG provides the necessary structure for determining the optimal cross-layer
actions in each time slot: the root packet in the DAG will always be selected
for transmission since it has the highest positive marginal utility; and the
complexity of the proposed cross-layer solution is demonstrated to linearly
increase w.r.t. the number of disconnected packet pairs in the DAG and
exponentially increase w.r.t. the number of packets on which the current
packets depend on. The simulation results demonstrate that the proposed
solution significantly outperforms existing state-of-the-art cross-layer
solutions. Moreover, we show that our solution provides the upper bound
performance for the cross-layer optimization solutions with delayed feedback
such as the well-known RaDiO framework.
|
0905.4091
|
Hybrid ARQ in Multiple-Antenna Slow Fading Channels: Performance Limits
and Optimal Linear Dispersion Code Design
|
cs.IT math.IT
|
This paper focuses on studying the fundamental performance limits and linear
dispersion code design for the MIMO-ARQ slow fading channel. Optimal average
rate of well-known HARQ protocols is analyzed. The optimal design of space-time
coding for the MIMO-ARQ channel is discussed. Information-theoretic measures
are used to optimize the rate assignment and derive the optimum design
criterion, which is then used to evaluate the optimality of existing space-time
codes. A different design criterion, which is obtained from the error
probability analysis of space-time coded MIMO-HARQ, is presented. Examples are
studied to reveal the gain of ARQ feedback in space-time coded MIMO systems.
|
0905.4138
|
Faster estimation of the correlation fractal dimension using
box-counting
|
cs.DB cs.DS
|
Fractal dimension is widely adopted in spatial databases and data mining,
among others as a measure of dataset skewness. State-of-the-art algorithms for
estimating the fractal dimension exhibit linear runtime complexity whether
based on box-counting or approximation schemes. In this paper, we revisit a
correlation fractal dimension estimation algorithm that redundantly rescans the
dataset and, extending that work, we propose another linear, yet faster and as
accurate method, which completes in a single pass.
|
0905.4160
|
Codes over Quaternion Integers with Respect to Lipschitz Metric
|
cs.IT math.IT
|
I want to withdraw this paper.
|
0905.4162
|
Google matrix, dynamical attractors and Ulam networks
|
cs.IR
|
We study the properties of the Google matrix generated by a coarse-grained
Perron-Frobenius operator of the Chirikov typical map with dissipation. The
finite size matrix approximant of this operator is constructed by the Ulam
method. This method applied to the simple dynamical model creates the directed
Ulam networks with approximate scale-free scaling and characteristics being
rather similar to those of the World Wide Web. The simple dynamical attractors
play here the role of popular web sites with a strong concentration of
PageRank. A variation of the Google parameter $\alpha$ or other parameters of
the dynamical map can drive the PageRank of the Google matrix to a delocalized
phase with a strange attractor where the Google search becomes inefficient.
|
0905.4163
|
Cyclic Codes over Some Finite Rings
|
cs.IT math.CO math.IT
|
In this paper cyclic codes are established with respect to the Mannheim
metric over some finite rings by using Gaussian integers and the decoding
algorithm for these codes is given.
|
0905.4164
|
Iterative Decoding on Multiple Tanner Graphs Using Random Edge Local
Complementation
|
cs.IT math.IT
|
In this paper, we propose to enhance the performance of the sum-product
algorithm (SPA) by interleaving SPA iterations with a random local graph update
rule. This rule is known as edge local complementation (ELC), and has the
effect of modifying the Tanner graph while preserving the code. We have
previously shown how the ELC operation can be used to implement an iterative
permutation group decoder (SPA-PD)--one of the most successful iterative
soft-decision decoding strategies at small blocklengths. In this work, we
exploit the fact that ELC can also give structurally distinct parity-check
matrices for the same code. Our aim is to describe a simple iterative decoder,
running SPA-PD on distinct structures, based entirely on random usage of the
ELC operation. This is called SPA-ELC, and we focus on small blocklength codes
with strong algebraic structure. In particular, we look at the extended Golay
code and two extended quadratic residue codes. Both error rate performance and
average decoding complexity, measured by the average total number of messages
required in the decoding, significantly outperform those of the standard SPA,
and compares well with SPA-PD. However, in contrast to SPA-PD, which requires a
global action on the Tanner graph, we obtain a performance improvement via
local action alone. Such localized algorithms are of mathematical interest in
their own right, but are also suited to parallel/distributed realizations.
|
0905.4165
|
Cyclic Codes over Some Finite Quaternion Integer Rings
|
cs.IT math.IT
|
In this paper, cyclic codes are established over some finite quaternion
integer rings with respect to the quaternion Mannheim distance, and de- coding
algorithm for these codes is given.
|
0905.4201
|
The Usefulness of Multilevel Hash Tables with Multiple Hash Functions in
Large Databases
|
cs.DS cs.DB
|
In this work, attempt is made to select three good hash functions which
uniformly distribute hash values that permute their internal states and allow
the input bits to generate different output bits. These functions are used in
different levels of hash tables that are coded in Java Programming Language and
a quite number of data records serve as primary data for testing the
performances. The result shows that the two-level hash tables with three
different hash functions give a superior performance over one-level hash table
with two hash functions or zero-level hash table with one function in term of
reducing the conflict keys and quick lookup for a particular element. The
result assists to reduce the complexity of join operation in query language
from O(n2) to O(1) by placing larger query result, if any, in multilevel hash
tables with multiple hash functions and generate shorter query result.
|
0905.4303
|
On Block Noncoherent Communication with Low-Precision Phase Quantization
at the Receiver
|
cs.IT math.IT
|
We consider communication over the block noncoherent AWGN channel with
low-precision Analog-to-Digital Converters (ADCs) at the receiver. For standard
uniform Phase Shift Keying (PSK) modulation, we investigate the performance of
a receiver architecture that quantizes only the phase of the received signal;
this has the advantage of being implementable without automatic gain control,
using multiple 1-bit ADCs preceded by analog multipliers. We study the
structure of the transition density of the resulting channel model. Several
results, based on the symmetry inherent in the channel, are provided to
characterize this transition density. A low complexity procedure for computing
the channel capacity is obtained using these results. Numerical capacity
computations for QPSK show that 8-bin phase quantization of the received signal
recovers more than 80-85 % of the capacity attained with unquantized
observations, while 12-bin phase quantization recovers above 90-95 % of the
unquantized capacity. Dithering the constellation is shown to improve the
performance in the face of drastic quantization.
|
0905.4341
|
Characterizing predictable classes of processes
|
cs.AI cs.IT math.IT math.PR
|
The problem is sequence prediction in the following setting. A sequence
$x_1,...,x_n,...$ of discrete-valued observations is generated according to
some unknown probabilistic law (measure) $\mu$. After observing each outcome,
it is required to give the conditional probabilities of the next observation.
The measure $\mu$ belongs to an arbitrary class $\C$ of stochastic processes.
We are interested in predictors $\rho$ whose conditional probabilities converge
to the "true" $\mu$-conditional probabilities if any $\mu\in\C$ is chosen to
generate the data. We show that if such a predictor exists, then a predictor
can also be obtained as a convex combination of a countably many elements of
$\C$. In other words, it can be obtained as a Bayesian predictor whose prior is
concentrated on a countable set. This result is established for two very
different measures of performance of prediction, one of which is very strong,
namely, total variation, and the other is very weak, namely, prediction in
expected average Kullback-Leibler divergence.
|
0905.4369
|
Automating Quantified Multimodal Logics in Simple Type Theory -- A Case
Study
|
cs.AI cs.LO
|
In a case study we investigate whether off the shelf higher-order theorem
provers and model generators can be employed to automate reasoning in and about
quantified multimodal logics. In our experiments we exploit the new TPTP
infrastructure for classical higher-order logic.
|
0905.4378
|
The Cramer-Rao Bound for Sparse Estimation
|
math.ST cs.IT math.IT stat.TH
|
The goal of this paper is to characterize the best achievable performance for
the problem of estimating an unknown parameter having a sparse representation.
Specifically, we consider the setting in which a sparsely representable
deterministic parameter vector is to be estimated from measurements corrupted
by Gaussian noise, and derive a lower bound on the mean-squared error (MSE)
achievable in this setting. To this end, an appropriate definition of bias in
the sparse setting is developed, and the constrained Cramer-Rao bound (CRB) is
obtained. This bound is shown to equal the CRB of an estimator with knowledge
of the support set, for almost all feasible parameter values. Consequently, in
the unbiased case, our bound is identical to the MSE of the oracle estimator.
Combined with the fact that the CRB is achieved at high signal-to-noise ratios
by the maximum likelihood technique, our result provides a new interpretation
for the common practice of using the oracle estimator as a gold standard
against which practical approaches are compared.
|
0905.4387
|
Information Modeling for a Dynamic Representation of an Emergency
Situation
|
cs.AI cs.MA
|
In this paper we propose an approach to build a decision support system that
can help emergency planners and responders to detect and manage emergency
situations. The internal mechanism of the system is independent from the
treated application. Therefore, we think the system may be used or adapted
easily to different case studies. We focus here on a first step in the
decision-support process which concerns the modeling of information issued from
the perceived environment and their representation dynamically using a
multiagent system. This modeling was applied on the RoboCupRescue Simulation
System. An implementation and some results are presented here.
|
0905.4476
|
Beacon-Assisted Spectrum Access with Cooperative Cognitive Transmitter
and Receiver
|
cs.IT math.IT
|
Spectrum access is an important function of cognitive radios for detecting
and utilizing spectrum holes without interfering with the legacy systems. In
this paper we propose novel cooperative communication models and show how
deploying such cooperations between a pair of secondary transmitter and
receiver assists them in identifying spectrum opportunities more reliably.
These cooperations are facilitated by dynamically and opportunistically
assigning one of the secondary users as a relay to assist the other one which
results in more efficient spectrum hole detection. Also, we investigate the
impact of erroneous detection of spectrum holes and thereof missing
communication opportunities on the capacity of the secondary channel. The
capacity of the secondary users with interference-avoiding spectrum access is
affected by 1) how effectively the availability of vacant spectrum is sensed by
the secondary transmitter-receiver pair, and 2) how correlated are the
perceptions of the secondary transmitter-receiver pair about network spectral
activity. We show that both factors are improved by using the proposed
cooperative protocols. One of the proposed protocols requires explicit
information exchange in the network. Such information exchange in practice is
prone to wireless channel errors (i.e., is imperfect) and costs bandwidth loss.
We analyze the effects of such imperfect information exchange on the capacity
as well as the effect of bandwidth cost on the achievable throughput. The
protocols are also extended to multiuser secondary networks.
|
0905.4482
|
Topics in Compressed Sensing
|
math.NA cs.IT math.IT
|
Compressed sensing has a wide range of applications that include error
correction, imaging, radar and many more. Given a sparse signal in a high
dimensional space, one wishes to reconstruct that signal accurately and
efficiently from a number of linear measurements much less than its actual
dimension. Although in theory it is clear that this is possible, the difficulty
lies in the construction of algorithms that perform the recovery efficiently,
as well as determining which kind of linear measurements allow for the
reconstruction. There have been two distinct major approaches to sparse
recovery that each present different benefits and shortcomings. The first,
L1-minimization methods such as Basis Pursuit, use a linear optimization
problem to recover the signal. This method provides strong guarantees and
stability, but relies on Linear Programming, whose methods do not yet have
strong polynomially bounded runtimes. The second approach uses greedy methods
that compute the support of the signal iteratively. These methods are usually
much faster than Basis Pursuit, but until recently had not been able to provide
the same guarantees. This gap between the two approaches was bridged when we
developed and analyzed the greedy algorithm Regularized Orthogonal Matching
Pursuit (ROMP). ROMP provides similar guarantees to Basis Pursuit as well as
the speed of a greedy algorithm. Our more recent algorithm Compressive Sampling
Matching Pursuit (CoSaMP) improves upon these guarantees, and is optimal in
every important aspect.
|
0905.4541
|
Turbo Packet Combining Strategies for the MIMO-ISI ARQ Channel
|
cs.IT math.IT
|
This paper addresses the issue of efficient turbo packet combining techniques
for coded transmission with a Chase-type automatic repeat request (ARQ)
protocol operating over a multiple-input--multiple-output (MIMO) channel with
intersymbol interference (ISI). First of all, we investigate the outage
probability and the outage-based power loss of the MIMO-ISI ARQ channel when
optimal maximum a posteriori (MAP) turbo packet combining is used at the
receiver. We show that the ARQ delay (i.e., the maximum number of ARQ rounds)
does not completely translate into a diversity gain. We then introduce two
efficient turbo packet combining algorithms that are inspired by minimum mean
square error (MMSE)-based turbo equalization techniques. Both schemes can be
viewed as low-complexity versions of the optimal MAP turbo combiner. The first
scheme is called signal-level turbo combining and performs packet combining and
multiple transmission ISI cancellation jointly at the signal-level. The second
scheme, called symbol-level turbo combining, allows ARQ rounds to be separately
turbo equalized, while combining is performed at the filter output. We conduct
a complexity analysis where we demonstrate that both algorithms have almost the
same computational cost as the conventional log-likelihood ratio (LLR)-level
combiner. Simulation results show that both proposed techniques outperform
LLR-level combining, while for some representative MIMO configurations,
signal-level combining has better ISI cancellation capability and achievable
diversity order than that of symbol-level combining.
|
0905.4545
|
Minimum Distance and Convergence Analysis of
Hamming-Accumulate-Acccumulate Codes
|
cs.IT math.IT
|
In this letter we consider the ensemble of codes formed by the serial
concatenation of a Hamming code and two accumulate codes. We show that this
ensemble is asymptotically good, in the sense that most codes in the ensemble
have minimum distance growing linearly with the block length. Thus, the
resulting codes achieve high minimum distances with high probability, about
half or more of the minimum distance of a typical random linear code of the
same rate and length in our examples. The proposed codes also show reasonably
good iterative convergence thresholds, which makes them attractive for
applications requiring high code rates and low error rates, such as optical
communications and magnetic recording.
|
0905.4570
|
Weak Evolvability Equals Strong Evolvability
|
cs.AI cs.NE
|
An updated version will be uploaded later.
|
0905.4601
|
Considerations on Construction Ontologies
|
cs.AI
|
The paper proposes an analysis on some existent ontologies, in order to point
out ways to resolve semantic heterogeneity in information systems. Authors are
highlighting the tasks in a Knowledge Acquisiton System and identifying aspects
related to the addition of new information to an intelligent system. A solution
is proposed, as a combination of ontology reasoning services and natural
languages generation. A multi-agent system will be conceived with an extractor
agent, a reasoner agent and a competence management agent.
|
0905.4605
|
Techniques for Securing Data Exchange between a Database Server and a
Client Program
|
cs.DB
|
The goal of the presented work is to illustrate a method by which the data
exchange between a standalone computer software and a shared database server
can be protected of unauthorized interceptation of the traffic in Internet
network, a transport network for data managed by those two systems,
interceptation by which an attacker could gain illegetimate access to the
database, threatening this way the data integrity and compromising the
database.
|
0905.4614
|
A Logic Programming Approach to Activity Recognition
|
cs.AI
|
We have been developing a system for recognising human activity given a
symbolic representation of video content. The input of our system is a set of
time-stamped short-term activities detected on video frames. The output of our
system is a set of recognised long-term activities, which are pre-defined
temporal combinations of short-term activities. The constraints on the
short-term activities that, if satisfied, lead to the recognition of a
long-term activity, are expressed using a dialect of the Event Calculus. We
illustrate the expressiveness of the dialect by showing the representation of
several typical complex activities. Furthermore, we present a detailed
evaluation of the system through experimentation on a benchmark dataset of
surveillance videos.
|
0905.4627
|
CoPhIR: a Test Collection for Content-Based Image Retrieval
|
cs.MM cs.IR
|
The scalability, as well as the effectiveness, of the different Content-based
Image Retrieval (CBIR) approaches proposed in literature, is today an important
research issue. Given the wealth of images on the Web, CBIR systems must in
fact leap towards Web-scale datasets. In this paper, we report on our
experience in building a test collection of 100 million images, with the
corresponding descriptive features, to be used in experimenting new scalable
techniques for similarity searching, and comparing their results. In the
context of the SAPIR (Search on Audio-visual content using Peer-to-peer
Information Retrieval) European project, we had to experiment our distributed
similarity searching technology on a realistic data set. Therefore, since no
large-scale collection was available for research purposes, we had to tackle
the non-trivial process of image crawling and descriptive feature extraction
(we used five MPEG-7 features) using the European EGEE computer GRID. The
result of this effort is CoPhIR, the first CBIR test collection of such scale.
CoPhIR is now open to the research community for experiments and comparisons,
and access to the collection was already granted to more than 50 research
groups worldwide.
|
0905.4656
|
Quantization Errors of fGn and fBm Signals
|
cs.IT math.IT
|
In this Letter, we show that under the assumption of high resolution, the
quantization errors of fGn and fBm signals with uniform quantizer can be
treated as uncorrelated white noises.
|
0905.4684
|
A Simple Sequential Spectrum Sensing Scheme for Cognitive Radio
|
cs.IT math.IT
|
Cognitive radio that supports a secondary and opportunistic access to
licensed spectrum shows great potential to dramatically improve spectrum
utilization. Spectrum sensing performed by secondary users to detect unoccupied
spectrum bands, is a key enabling technique for cognitive radio. This paper
proposes a truncated sequential spectrum sensing scheme, namely the sequential
shifted chi-square test (SSCT). The SSCT has a simple test statistic and does
not rely on any deterministic knowledge about primary signals. As figures of
merit, the exact false-alarm probability is derived, and the miss-detection
probability as well as the average sample number (ASN) are evaluated by using a
numerical integration algorithm. Corroborating numerical examples show that, in
comparison with fixed-sample size detection schemes such as energy detection,
the SSCT delivers considerable reduction on the ASN while maintaining a
comparable detection performance.
|
0905.4700
|
Cross-Layer Design of FDD-OFDM Systems based on ACK/NAK Feedbacks
|
cs.IT math.IT
|
It is well-known that cross-layer scheduling which adapts power, rate and
user allocation can achieve significant gain on system capacity. However,
conventional cross-layer designs all require channel state information at the
base station (CSIT) which is difficult to obtain in practice. In this paper, we
focus on cross-layer resource optimization based on ACK/NAK feedback flows in
OFDM systems without explicit CSIT. While the problem can be modeled as Markov
Decision Process (MDP), brute force approach by policy iteration or value
iteration cannot lead to any viable solution. Thus, we derive a simple
closed-form solution for the MDP cross-layer problem, which is asymptotically
optimal for sufficiently small target packet error rate (PER). The proposed
solution also has low complexity and is suitable for realtime implementation.
It is also shown to achieve significant performance gain compared with systems
that do not utilize the ACK/NAK feedbacks for cross-layer designs or
cross-layer systems that utilize very unreliable CSIT for adaptation with
mismatch in CSIT error statistics. Asymptotic analysis is also provided to
obtain useful design insights.
|
0905.4713
|
Mining Generalized Patterns from Large Databases using Ontologies
|
cs.AI cs.DB cs.DM
|
Formal Concept Analysis (FCA) is a mathematical theory based on the
formalization of the notions of concept and concept hierarchies. It has been
successfully applied to several Computer Science fields such as data
mining,software engineering, and knowledge engineering, and in many domains
like medicine, psychology, linguistics and ecology. For instance, it has been
exploited for the design, mapping and refinement of ontologies. In this paper,
we show how FCA can benefit from a given domain ontology by analyzing the
impact of a taxonomy (on objects and/or attributes) on the resulting concept
lattice. We willmainly concentrate on the usage of a taxonomy to extract
generalized patterns (i.e., knowledge generated from data when elements of a
given domain ontology are used) in the form of concepts and rules, and improve
navigation through these patterns. To that end, we analyze three generalization
cases and show their impact on the size of the generalized pattern set.
Different scenarios of simultaneous generalizations on both objects and
attributes are also discussed
|
0905.4757
|
Stochastic Optimization for Markov Modulated Networks with Application
to Delay Constrained Wireless Scheduling
|
math.OC cs.SY
|
We consider a wireless system with a small number of delay constrained users
and a larger number of users without delay constraints. We develop a scheduling
algorithm that reacts to time varying channels and maximizes throughput utility
(to within a desired proximity), stabilizes all queues, and satisfies the delay
constraints. The problem is solved by reducing the constrained optimization to
a set of weighted stochastic shortest path problems, which act as natural
generalizations of max-weight policies to Markov decision networks. We also
present approximation results for the corresponding shortest path problems, and
discuss the additional complexity and delay incurred as compared to systems
without delay constraints. The solution technique is general and applies to
other constrained stochastic decision problems.
|
0905.4761
|
Optimizing XML Compression
|
cs.DB
|
The eXtensible Markup Language (XML) provides a powerful and flexible means
of encoding and exchanging data. As it turns out, its main advantage as an
encoding format (namely, its requirement that all open and close markup tags
are present and properly balanced) yield also one of its main disadvantages:
verbosity. XML-conscious compression techniques seek to overcome this drawback.
Many of these techniques first separate XML structure from the document
content, and then compress each independently. Further compression gains can be
realized by identifying and compressing together document content that is
highly similar, thereby amortizing the storage costs of auxiliary information
required by the chosen compression algorithm. Additionally, the proper choice
of compression algorithm is an important factor not only for the achievable
compression gain, but also for access performance. Hence, choosing a
compression configuration that optimizes compression gain requires one to
determine (1) a partitioning strategy for document content, and (2) the best
available compression algorithm to apply to each set within this partition. In
this paper, we show that finding an optimal compression configuration with
respect to compression gain is an NP-hard optimization problem. This problem
remains intractable even if one considers a single compression algorithm for
all content. We also describe an approximation algorithm for selecting a
partitioning strategy for document content based on the branch-and-bound
paradigm.
|
0905.4771
|
Variational structure of the optimal artificial diffusion method for the
advection-diffusion equation
|
cs.CE cs.NA
|
In this research note we provide a variational basis for the optimal
artificial diffusion method, which has been a cornerstone in developing many
stabilized methods. The optimal artificial diffusion method produces exact
nodal solutions when applied to one-dimensional problems with constant
coefficients and forcing function. We first present a variational principle for
a multi-dimensional advective-diffusive system, and then derive a new stable
weak formulation. When applied to one-dimensional problems with constant
coefficients and forcing function, this resulting weak formulation will be
equivalent to the optimal artificial diffusion method. We present
representative numerical results to corroborate our theoretical findings.
|
0905.4918
|
Divide and Conquer: Partitioning Online Social Networks
|
cs.NI cs.AI cs.DC
|
Online Social Networks (OSNs) have exploded in terms of scale and scope over
the last few years. The unprecedented growth of these networks present
challenges in terms of system design and maintenance. One way to cope with this
is by partitioning such large networks and assigning these partitions to
different machines. However, social networks possess unique properties that
make the partitioning problem non-trivial. The main contribution of this paper
is to understand different properties of social networks and how these
properties can guide the choice of a partitioning algorithm. Using large scale
measurements representing real OSNs, we first characterize different properties
of social networks, and then we evaluate qualitatively different partitioning
methods that cover the design space. We expose different trade-offs involved
and understand them in light of properties of social networks. We show that a
judicious choice of a partitioning scheme can help improve performance.
|
0905.4926
|
On Node Density -- Outage Probability Tradeoff in Wireless Networks
|
cs.IT math.IT
|
A statistical model of interference in wireless networks is considered, which
is based on the traditional propagation channel model and a Poisson model of
random spatial distribution of nodes in 1-D, 2-D and 3-D spaces with both
uniform and non-uniform densities. The power of nearest interferer is used as a
major performance indicator, instead of a traditionally-used total interference
power, since at the low outage region, they have the same statistics so that
the former is an accurate approximation of the latter. This simplifies the
problem significantly and allows one to develop a unified framework for the
outage probability analysis, including the impacts of complete/partial
interference cancelation, of different types of fading and of linear filtering,
either alone or in combination with each other. When a given number of nearest
interferers are completely canceled, the outage probability is shown to scale
down exponentially in this number. Three different models of partial
cancelation are considered and compared via their outage probabilities. The
partial cancelation level required to eliminate the impact of an interferer is
quantified. The effect of a broad class of fading processes (including all
popular fading models) is included in the analysis in a straightforward way,
which can be positive or negative depending on a particular model and
propagation/system parameters. The positive effect of linear filtering (e.g. by
directional antennas) is quantified via a new statistical selectivity
parameter. The analysis results in formulation of a tradeoff relationship
between the network density and the outage probability, which is a result of
the interplay between random geometry of node locations, the propagation path
loss and the distortion effects at the victim receiver.
|
0905.4937
|
A criterion for hypothesis testing for stationary processes
|
math.ST cs.IT math.IT math.PR stat.TH
|
Given a finite-valued sample $X_1,...,X_n$ we wish to test whether it was
generated by a stationary ergodic process belonging to a family $H_0$, or it
was generated by a stationary ergodic process outside $H_0$. We require the
Type I error of the test to be uniformly bounded, while the type II error has
to be mande not more than a finite number of times with probability 1. For this
notion of consistency we provide necessary and sufficient conditions on the
family $H_0$ for the existence of a consistent test. This criterion is
illustrated with applications to testing for a membership to parametric
families, generalizing some existing results. In addition, we analyze a
stronger notion of consistency, which requires finite-sample guarantees on
error of both types, and provide some necessary and some sufficient conditions
for the existence of a consistent test. We emphasize that no assumption on the
process distributions are made beyond stationarity and ergodicity.
|
0906.0037
|
Asymptotic Capacity and Optimal Precoding in MIMO Multi-Hop Relay
Networks
|
cs.IT math.IT
|
A multi-hop relaying system is analyzed where data sent by a multi-antenna
source is relayed by successive multi-antenna relays until it reaches a
multi-antenna destination. Assuming correlated fading at each hop, each relay
receives a faded version of the signal from the previous level, performs linear
precoding and retransmits it to the next level. Using free probability theory
and assuming that the noise power at relaying levels-- but not at destination--
is negligible, the closed-form expression of the asymptotic instantaneous
end-to-end mutual information is derived as the number of antennas at all
levels grows large. The so-obtained deterministic expression is independent
from the channel realizations while depending only on channel statistics.
Moreover, it also serves as the asymptotic value of the average end-to-end
mutual information. The optimal singular vectors of the precoding matrices that
maximize the average mutual information with finite number of antennas at all
levels are also provided. It turns out that the optimal precoding singular
vectors are aligned to the eigenvectors of the channel correlation matrices.
Thus they can be determined using only the known channel statistics. As the
optimal precoding singular vectors are independent from the system size, they
are also optimal in the asymptotic regime.
|
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