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1103.4086
|
Lattice Codes for the Wiretap Gaussian Channel: Construction and
Analysis
|
cs.IT math.IT
|
We consider the Gaussian wiretap channel, where two legitimate players Alice
and Bob communicate over an additive white Gaussian noise (AWGN) channel, while
Eve is eavesdropping, also through an AWGN channel. We propose a coding
strategy based on lattice coset encoding. We analyze Eve's probability of
decoding, from which we define the secrecy gain as a design criterion for
wiretap lattice codes, expressed in terms of the lattice theta series, which
characterizes Eve's confusion as a function of the channel parameters. The
secrecy gain is studied for even unimodular lattices, and an asymptotic
analysis shows that it grows exponentially in the dimension of the lattice.
Examples of wiretap lattice codes are given. Interestingly, minimizing Eve's
probability of error involves the same optimization of the theta series as does
the flatness factor, another newly defined code design that characterizes
lattice codes that achieve strong secrecy.
|
1103.4090
|
A Linear Classifier Based on Entity Recognition Tools and a Statistical
Approach to Method Extraction in the Protein-Protein Interaction Literature
|
q-bio.QM cs.CL cs.IR cs.LG
|
We participated, in the Article Classification and the Interaction Method
subtasks (ACT and IMT, respectively) of the Protein-Protein Interaction task of
the BioCreative III Challenge. For the ACT, we pursued an extensive testing of
available Named Entity Recognition and dictionary tools, and used the most
promising ones to extend our Variable Trigonometric Threshold linear
classifier. For the IMT, we experimented with a primarily statistical approach,
as opposed to employing a deeper natural language processing strategy. Finally,
we also studied the benefits of integrating the method extraction approach that
we have used for the IMT into the ACT pipeline. For the ACT, our linear article
classifier leads to a ranking and classification performance significantly
higher than all the reported submissions. For the IMT, our results are
comparable to those of other systems, which took very different approaches. For
the ACT, we show that the use of named entity recognition tools leads to a
substantial improvement in the ranking and classification of articles relevant
to protein-protein interaction. Thus, we show that our substantially expanded
linear classifier is a very competitive classifier in this domain. Moreover,
this classifier produces interpretable surfaces that can be understood as
"rules" for human understanding of the classification. In terms of the IMT
task, in contrast to other participants, our approach focused on identifying
sentences that are likely to bear evidence for the application of a PPI
detection method, rather than on classifying a document as relevant to a
method. As BioCreative III did not perform an evaluation of the evidence
provided by the system, we have conducted a separate assessment; the evaluators
agree that our tool is indeed effective in detecting relevant evidence for PPI
detection methods.
|
1103.4168
|
Caching in Multidimensional Databases
|
cs.DB
|
One utilisation of multidimensional databases is the field of On-line
Analytical Processing (OLAP). The applications in this area are designed to
make the analysis of shared multidimensional information fast [9]. On one hand,
speed can be achieved by specially devised data structures and algorithms. On
the other hand, the analytical process is cyclic. In other words, the user of
the OLAP application runs his or her queries one after the other. The output of
the last query may be there (at least partly) in one of the previous results.
Therefore caching also plays an important role in the operation of these
systems. However, caching itself may not be enough to ensure acceptable
performance. Size does matter: The more memory is available, the more we gain
by loading and keeping information in there. Oftentimes, the cache size is
fixed. This limits the performance of the multidimensional database, as well,
unless we compress the data in order to move a greater proportion of them into
the memory. Caching combined with proper compression methods promise further
performance improvements. In this paper, we investigate how caching influences
the speed of OLAP systems. Different physical representations (multidimensional
and table) are evaluated. For the thorough comparison, models are proposed. We
draw conclusions based on these models, and the conclusions are verified with
empirical data.
|
1103.4169
|
Difference-Huffman Coding of Multidimensional Databases
|
cs.DB
|
A new compression method called difference-Huffman coding (DHC) is introduced
in this paper. It is verified empirically that DHC results in a smaller
multidimensional physical representation than those for other previously
published techniques (single count header compression, logical position
compression, base-offset compression and difference sequence compression). The
article examines how caching influences the expected retrieval time of the
multidimensional and table representations of relations. A model is proposed
for this, which is then verified with empirical data. Conclusions are drawn,
based on the model and the experiment, about when one physical representation
outperforms another in terms of retrieval time. Over the tested range of
available memory, the performance for the multidimensional representation was
always much quicker than for the table representation.
|
1103.4177
|
On the Capacity of the Noncausal Relay Channel
|
cs.IT math.IT
|
This paper studies the noncausal relay channel, also known as the relay
channel with unlimited lookahead, introduced by El Gamal, Hassanpour, and
Mammen. Unlike the standard relay channel model, where the relay encodes its
signal based on the previous received output symbols, the relay in the
noncausal relay channel encodes its signal as a function of the entire received
sequence. In the existing coding schemes, the relay uses this noncausal
information solely to recover the transmitted message and then cooperates with
the sender to communicate this message to the receiver. However, it is shown in
this paper that by applying the Gelfand--Pinsker coding scheme, the relay can
take further advantage of the noncausally available information, which can
achieve strictly higher rates than existing coding schemes. This paper also
provides a new upper bound on the capacity of the noncausal relay that strictly
improves upon the cutset bound. These new lower and upper bounds on the
capacity coincide for the class of degraded noncausal relay channels and
establish the capacity for this class.
|
1103.4198
|
Continuous-time performance limitations for overshoot and resulted
tracking measures
|
math.OC cs.SY
|
A dual formulation for the problem of determining absolute performance
limitations on overshoot, undershoot, maximum amplitude and fluctuation
minimization for continuous-time feedback systems is constructed. Determining,
for example, the minimum possible overshoot attainable by all possible
stabilizing controllers is an optimization task that cannot be expressed as a
minimum-norm problem. It is this fact, coupled with the continuous-time rather
than discrete-time formulation, that makes these problems challenging. We
extend previous results to include more general reference functions, and derive
new results (in continuous time) on the influence of pole/zero locations on
achievable time-domain performance.
|
1103.4204
|
Parallel Online Learning
|
cs.LG
|
In this work we study parallelization of online learning, a core primitive in
machine learning. In a parallel environment all known approaches for parallel
online learning lead to delayed updates, where the model is updated using
out-of-date information. In the worst case, or when examples are temporally
correlated, delay can have a very adverse effect on the learning algorithm.
Here, we analyze and present preliminary empirical results on a set of learning
architectures based on a feature sharding approach that present various
tradeoffs between delay, degree of parallelism, representation power and
empirical performance.
|
1103.4223
|
A Stochastic-Geometry Approach to Coverage in Cellular Networks with
Multi-Cell Cooperation
|
cs.IT math.IT
|
Multi-cell cooperation is a promising approach for mitigating inter-cell
interference in dense cellular networks. Quantifying the performance of
multi-cell cooperation is challenging as it integrates physical-layer
techniques and network topologies. For tractability, existing work typically
relies on the over-simplified Wyner-type models. In this paper, we propose a
new stochastic-geometry model for a cellular network with multi-cell
cooperation, which accounts for practical factors including the irregular
locations of base stations (BSs) and the resultant path-losses. In particular,
the proposed network-topology model has three key features: i) the cells are
modeled using a Poisson random tessellation generated by Poisson distributed
BSs, ii) multi-antenna BSs are clustered using a hexagonal lattice and BSs in
the same cluster mitigate mutual interference by spatial interference
avoidance, iii) BSs near cluster edges access a different sub-channel from that
by other BSs, shielding cluster-edge mobiles from strong interference. Using
this model and assuming sparse scattering, we analyze the shapes of the outage
probabilities of mobiles served by cluster-interior BSs as the average number
$K$ of BSs per cluster increases. The outage probability of a mobile near a
cluster center is shown to be proportional to $e^{-c(2-\sqrt{\nu})^2K}$ where
$\nu$ is the fraction of BSs lying in the interior of clusters and $c$ is a
constant. Moreover, the outage probability of a typical mobile is proved to
scale proportionally with $e^{-c' (1-\sqrt{\nu})^2K}$ where $c'$ is a constant.
|
1103.4282
|
Stratified B-trees and versioning dictionaries
|
cs.DS cs.DB
|
A classic versioned data structure in storage and computer science is the
copy-on-write (CoW) B-tree -- it underlies many of today's file systems and
databases, including WAFL, ZFS, Btrfs and more. Unfortunately, it doesn't
inherit the B-tree's optimality properties; it has poor space utilization,
cannot offer fast updates, and relies on random IO to scale. Yet, nothing
better has been developed since. We describe the `stratified B-tree', which
beats all known semi-external memory versioned B-trees, including the CoW
B-tree. In particular, it is the first versioned dictionary to achieve optimal
tradeoffs between space, query and update performance.
|
1103.4286
|
Design and frequency analysis of continuous finite-time-convergent
differentiator
|
cs.SY math.DS math.OC
|
In this paper, a continuous finite-time-convergent differentiator is
presented based on a strong Lyapunov function. The continuous differentiator
can reduce chattering phenomenon sufficiently than normal sliding mode
differentiator, and the outputs of signal tracking and derivative estimation
are all smooth. Frequency analysis is applied to compare the continuous
differentiator with sliding mode differentiator. The beauties of the continuous
finite-time-convergent differentiator include its simplicity, restraining
noises sufficiently, and avoiding the chattering phenomenon.
|
1103.4311
|
Design and analysis of continuous hybrid differentiator
|
cs.SY math.DS math.OC
|
In this paper, a continuous hybrid differentiator is presented based on a
strong Lyapunov function. The differentiator design can not only reduce
sufficiently chattering phenomenon of derivative estimation by introducing a
perturbation parameter, but also the dynamical performances are improved by
adding linear correction terms to the nonlinear ones. Moreover, strong
robustness ability is obtained by integrating sliding mode items and the linear
filter. Frequency analysis is applied to compare the hybrid continuous
differentiator with sliding mode differentiator. The merits of the continuous
hybrid differentiator include the excellent dynamical performances, restraining
noises sufficiently, and avoiding the chattering phenomenon.
|
1103.4335
|
Diviseurs de la forme 2D-G sans sections et rang de la multiplication
dans les corps finis (Divisors of the form 2D-G without sections and bilinear
complexity of multiplication in finite fields)
|
math.AG cs.CC cs.IT math.IT math.NT
|
Let X be an algebraic curve, defined over a perfect field, and G a divisor on
X. If X has sufficiently many points, we show how to construct a divisor D on X
such that l(2D-G)=0, of essentially any degree such that this is compatible the
Riemann-Roch theorem. We also generalize this construction to the case of a
finite number of constraints, l(k_i.D-G_i)=0, where |k_i|\leq 2.
Such a result was previously claimed by Shparlinski-Tsfasman-Vladut, in
relation with the Chudnovsky-Chudnovsky method for estimating the bilinear
complexity of the multiplication in finite fields based on interpolation on
curves; unfortunately, as noted by Cascudo et al., their proof was flawed. So
our work fixes the proof of Shparlinski-Tsfasman-Vladut and shows that their
estimate m_q\leq 2(1+1/(A(q)-1)) holds, at least when A(q)\geq 5. We also fix a
statement of Ballet that suffers from the same problem, and then we point out a
few other possible applications.
|
1103.4339
|
Optimal allocation patterns and optimal seed mass of a perennial plant
|
q-bio.PE cs.SY math.OC
|
We present a novel optimal allocation model for perennial plants, in which
assimilates are not allocated directly to vegetative or reproductive parts but
instead go first to a storage compartment from where they are then optimally
redistributed. We do not restrict considerations purely to periods favourable
for photosynthesis, as it was done in published models of perennial species,
but analyse the whole life period of a perennial plant. As a result, we obtain
the general scheme of perennial plant development, for which annual and
monocarpic strategies are special cases.
We not only re-derive predictions from several previous optimal allocation
models, but also obtain more information about plants' strategies during
transitions between favourable and unfavourable seasons. One of the model's
predictions is that a plant can begin to re-establish vegetative tissues from
storage, some time before the beginning of favourable conditions, which in turn
allows for better production potential when conditions become better. By means
of numerical examples we show that annual plants with single or multiple
reproduction periods, monocarps, evergreen perennials and polycarpic perennials
can be studied successfully with the help of our unified model.
Finally, we build a bridge between optimal allocation models and models
describing trade-offs between size and the number of seeds: a modelled plant
can control the distribution of not only allocated carbohydrates but also seed
size. We provide sufficient conditions for the optimality of producing the
smallest and largest seeds possible.
|
1103.4340
|
Fault Tolerant Stabilizability of Multi-Hop Control Networks
|
math.OC cs.SY
|
A Multi-hop Control Network (MCN) consists of a plant where the communication
between sensor, actuator and computational unit is supported by a wireless
multi-hop communication network, and data flow is performed using scheduling
and routing of sensing and actuation data. We address the problem of
characterizing controllability and observability of a MCN, by means of
necessary and sufficient conditions on the plant dynamics and on the
communication scheduling and routing. We provide a methodology to design
scheduling and routing, in order to satisfy controllability and observability
of a MCN for any fault occurrence in a given set of configurations of failures.
|
1103.4342
|
MDP Optimal Control under Temporal Logic Constraints
|
cs.RO cs.SY math.OC
|
In this paper, we develop a method to automatically generate a control policy
for a dynamical system modeled as a Markov Decision Process (MDP). The control
specification is given as a Linear Temporal Logic (LTL) formula over a set of
propositions defined on the states of the MDP. We synthesize a control policy
such that the MDP satisfies the given specification almost surely, if such a
policy exists. In addition, we designate an "optimizing proposition" to be
repeatedly satisfied, and we formulate a novel optimization criterion in terms
of minimizing the expected cost in between satisfactions of this proposition.
We propose a sufficient condition for a policy to be optimal, and develop a
dynamic programming algorithm that synthesizes a policy that is optimal under
some conditions, and sub-optimal otherwise. This problem is motivated by
robotic applications requiring persistent tasks, such as environmental
monitoring or data gathering, to be performed.
|
1103.4358
|
Selfishness, fraternity, and other-regarding preference in spatial
evolutionary games
|
physics.soc-ph cs.SI q-bio.PE
|
Spatial evolutionary games are studied with myopic players whose payoff
interest, as a personal character, is tuned from selfishness to other-regarding
preference via fraternity. The players are located on a square lattice and
collect income from symmetric two-person two-strategy (called cooperation and
defection) games with their nearest neighbors. During the elementary steps of
evolution a randomly chosen player modifies her strategy in order to maximize
stochastically her utility function composed from her own and the co-players'
income with weight factors $1-Q$ and Q. These models are studied within a wide
range of payoff parameters using Monte Carlo simulations for noisy strategy
updates and by spatial stability analysis in the low noise limit. For fraternal
players ($Q=1/2$) the system evolves into ordered arrangements of strategies in
the low noise limit in a way providing optimum payoff for the whole society.
Dominance of defectors, representing the "tragedy of the commons", is found
within the regions of prisoner's dilemma and stag hunt game for selfish players
(Q=0). Due to the symmetry in the effective utility function the system
exhibits similar behavior even for Q=1 that can be interpreted as the "lovers'
dilemma".
|
1103.4395
|
On Non-Bayesian Social Learning
|
cs.SI physics.soc-ph
|
We study a model of information aggregation and social learning recently
proposed by Jadbabaie, Sandroni, and Tahbaz-Salehi, in which individual agents
try to learn a correct state of the world by iteratively updating their beliefs
using private observations and beliefs of their neighbors. No individual
agent's private signal might be informative enough to reveal the unknown state.
As a result, agents share their beliefs with others in their social
neighborhood to learn from each other. At every time step each agent receives a
private signal, and computes a Bayesian posterior as an intermediate belief.
The intermediate belief is then averaged with the belief of neighbors to form
the individual's belief at next time step. We find a set of minimal sufficient
conditions under which the agents will learn the unknown state and reach
consensus on their beliefs without any assumption on the private signal
structure. The key enabler is a result that shows that using this update,
agents will eventually forecast the indefinite future correctly.
|
1103.4401
|
On the gradual deployment of random pairwise key distribution schemes
(Extended Version)
|
cs.CR cs.DM cs.IT math.IT
|
In the context of wireless sensor networks, the pairwise key distribution
scheme of Chan et al. has several advantages over other key distribution
schemes including the original scheme of Eschenauer and Gligor. However, this
offline pairwise key distribution mechanism requires that the network size be
set in advance, and involves all sensor nodes simultaneously. Here, we address
this issue by describing an implementation of the pairwise scheme that supports
the gradual deployment of sensor nodes in several consecutive phases. We
discuss the key ring size needed to maintain the secure connectivity throughout
all the deployment phases. In particular we show that the number of keys at
each sensor node can be taken to be $O(\log n)$ in order to achieve secure
connectivity (with high probability).
|
1103.4406
|
Interference Alignment with Partially Coordinated Transmit Precoding
|
cs.IT math.IT
|
In this paper, we introduce an efficient interference alignment (IA)
algorithm exploiting partially coordinated transmit precoding to improve the
number of concurrent interference-free transmissions, i.e., the multiplexing
gain, in multicell downlink. The proposed coordination model is such that each
base-station simultaneously transmits to two users and each user is served by
two base-stations. First, we show in a K-user system operating at the
information theoretic upper bound of degrees of freedom (DOF), the generic IA
is proper when $K \leq 3$, whereas the proposed partially coordinated IA is
proper when $K \leq 5$. Then, we derive a non-iterative, i.e., one shot, IA
algorithm for the proposed scheme when $K \leq 5$. We show that for a given
latency, the backhaul data rate requirement of the proposed method grows
linearly with K. Monte-Carlo simulation results show that the proposed one-shot
algorithm offers higher system throughput than the iterative IA at practical
SNR levels.
|
1103.4410
|
Distributed Inference and Query Processing for RFID Tracking and
Monitoring
|
cs.DB
|
In this paper, we present the design of a scalable, distributed stream
processing system for RFID tracking and monitoring. Since RFID data lacks
containment and location information that is key to query processing, we
propose to combine location and containment inference with stream query
processing in a single architecture, with inference as an enabling mechanism
for high-level query processing. We further consider challenges in
instantiating such a system in large distributed settings and design techniques
for distributed inference and query processing. Our experimental results, using
both real-world data and large synthetic traces, demonstrate the accuracy,
efficiency, and scalability of our proposed techniques.
|
1103.4435
|
Information Theoretic Bounds for Tensor Rank Minimization over Finite
Fields
|
cs.IT math.IT
|
We consider the problem of noiseless and noisy low-rank tensor completion
from a set of random linear measurements. In our derivations, we assume that
the entries of the tensor belong to a finite field of arbitrary size and that
reconstruction is based on a rank minimization framework. The derived results
show that the smallest number of measurements needed for exact reconstruction
is upper bounded by the product of the rank, the order and the dimension of a
cubic tensor. Furthermore, this condition is also sufficient for unique
minimization. Similar bounds hold for the noisy rank minimization scenario,
except for a scaling function that depends on the channel error probability.
|
1103.4438
|
Anytime Reliable Codes for Stabilizing Plants over Erasure Channels
|
cs.SY cs.IT math.IT math.OC
|
The problem of stabilizing an unstable plant over a noisy communication link
is an increasingly important one that arises in problems of distributed control
and networked control systems. Although the work of Schulman and Sahai over the
past two decades, and their development of the notions of "tree codes" and
"anytime capacity", provides the theoretical framework for studying such
problems, there has been scant practical progress in this area because explicit
constructions of tree codes with efficient encoding and decoding did not exist.
To stabilize an unstable plant driven by bounded noise over a noisy channel one
needs real-time encoding and real-time decoding and a reliability which
increases exponentially with delay, which is what tree codes guarantee. We
prove the existence of linear tree codes with high probability and, for erasure
channels, give an explicit construction with an expected encoding and decoding
complexity that is constant per time instant. We give sufficient conditions on
the rate and reliability required of the tree codes to stabilize vector plants
and argue that they are asymptotically tight. This work takes a major step
towards controlling plants over noisy channels, and we demonstrate the efficacy
of the method through several examples.
|
1103.4454
|
Regularity Results for Eikonal-Type Equations with Nonsmooth
Coefficients
|
math.OC cs.SY math.AP
|
Solutions of the Hamilton-Jacobi equation $H(x,-Du(x))=1$, with $H(\cdot,p)$
H\"older continuous and $H(x,\cdot)$ convex and positively homogeneous of
degree 1, are shown to be locally semiconcave with a power-like modulus. An
essential step of the proof is the ${\mathcal C}^{1,\alpha}$-regularity of the
extremal trajectories associated with the multifunction generated by $D_pH$.
|
1103.4480
|
Clustered regression with unknown clusters
|
cs.LG stat.ML
|
We consider a collection of prediction experiments, which are clustered in
the sense that groups of experiments ex- hibit similar relationship between the
predictor and response variables. The experiment clusters as well as the
regres- sion relationships are unknown. The regression relation- ships define
the experiment clusters, and in general, the predictor and response variables
may not exhibit any clus- tering. We call this prediction problem clustered
regres- sion with unknown clusters (CRUC) and in this paper we focus on linear
regression. We study and compare several methods for CRUC, demonstrate their
applicability to the Yahoo Learning-to-rank Challenge (YLRC) dataset, and in-
vestigate an associated mathematical model. CRUC is at the crossroads of many
prior works and we study several prediction algorithms with diverse origins: an
adaptation of the expectation-maximization algorithm, an approach in- spired by
K-means clustering, the singular value threshold- ing approach to matrix rank
minimization under quadratic constraints, an adaptation of the Curds and Whey
method in multiple regression, and a local regression (LoR) scheme reminiscent
of neighborhood methods in collaborative filter- ing. Based on empirical
evaluation on the YLRC dataset as well as simulated data, we identify the LoR
method as a good practical choice: it yields best or near-best prediction
performance at a reasonable computational load, and it is less sensitive to the
choice of the algorithm parameter. We also provide some analysis of the LoR
method for an asso- ciated mathematical model, which sheds light on optimal
parameter choice and prediction performance.
|
1103.4487
|
Handwritten Digit Recognition with a Committee of Deep Neural Nets on
GPUs
|
cs.LG cs.AI cs.CV cs.NE
|
The competitive MNIST handwritten digit recognition benchmark has a long
history of broken records since 1998. The most recent substantial improvement
by others dates back 7 years (error rate 0.4%) . Recently we were able to
significantly improve this result, using graphics cards to greatly speed up
training of simple but deep MLPs, which achieved 0.35%, outperforming all the
previous more complex methods. Here we report another substantial improvement:
0.31% obtained using a committee of MLPs.
|
1103.4525
|
Robust Lattice Alignment for K-user MIMO Interference Channels with
Imperfect Channel Knowledge
|
cs.IT math.IT
|
In this paper, we consider a robust lattice alignment design for K-user
quasi-static MIMO interference channels with imperfect channel knowledge. With
random Gaussian inputs, the conventional interference alignment (IA) method has
the feasibility problem when the channel is quasi-static. On the other hand,
structured lattices can create structured interference as opposed to the random
interference caused by random Gaussian symbols. The structured interference
space can be exploited to transmit the desired signals over the gaps. However,
the existing alignment methods on the lattice codes for quasi-static channels
either require infinite SNR or symmetric interference channel coefficients.
Furthermore, perfect channel state information (CSI) is required for these
alignment methods, which is difficult to achieve in practice. In this paper, we
propose a robust lattice alignment method for quasi-static MIMO interference
channels with imperfect CSI at all SNR regimes, and a two-stage decoding
algorithm to decode the desired signal from the structured interference space.
We derive the achievable data rate based on the proposed robust lattice
alignment method, where the design of the precoders, decorrelators, scaling
coefficients and interference quantization coefficients is jointly formulated
as a mixed integer and continuous optimization problem. The effect of imperfect
CSI is also accommodated in the optimization formulation, and hence the derived
solution is robust to imperfect CSI. We also design a low complex iterative
optimization algorithm for our robust lattice alignment method by using the
existing iterative IA algorithm that was designed for the conventional IA
method. Numerical results verify the advantages of the proposed robust lattice
alignment method.
|
1103.4547
|
Canonical Dual Method for Resource Allocation and Adaptive Modulation in
Uplink SC-FDMA Systems
|
cs.IT math.IT
|
In this paper, we study resource allocation and adaptive modulation in
SC-FDMA which is adopted as the multiple access scheme for the uplink in the
3GPP-LTE standard. A sum-utility maximization (SUmax), and a joint adaptive
modulation and sum-cost minimization (JAMSCmin) problems are considered. Unlike
OFDMA, in addition to the restriction of allocating a sub-channel to one user
at most, the multiple sub-channels allocated to a user in SC-FDMA should be
consecutive as well. This renders the resource allocation problem prohibitively
difficult and the standard optimization tools (e.g., Lagrange dual approach
widely used for OFDMA, etc.) can not help towards its optimal solution. We
propose a novel optimization framework for the solution of these problems that
is inspired from the recently developed canonical duality theory. We first
formulate the optimization problems as binary-integer programming problems and
then transform these binary-integer programming problems into continuous space
canonical dual problems that are concave maximization problems. Based on the
solution of the continuous space dual problems, we derive resource allocation
(joint with adaptive modulation for JAMSCmin) algorithms for both the problems
which have polynomial complexities. We provide conditions under which the
proposed algorithms are optimal. We also propose an adaptive modulation scheme
for SUmax problem. We compare the proposed algorithms with the existing
algorithms in the literature to assess their performance.
|
1103.4550
|
Community Detection via Semi-Synchronous Label Propagation Algorithms
|
cs.SI physics.soc-ph
|
A recently introduced novel community detection strategy is based on a label
propagation algorithm (LPA) which uses the diffusion of information in the
network to identify communities. Studies of LPAs showed that the strategy is
effective in finding a good community structure. Label propagation step can be
performed in parallel on all nodes (synchronous model) or sequentially
(asynchronous model); both models present some drawback, e.g., algorithm
termination is nor granted in the first case, performances can be worst in the
second case. In this paper, we present a semi-synchronous version of LPA which
aims to combine the advantages of both synchronous and asynchronous models. We
prove that our models always converge to a stable labeling. Moreover, we
experimentally investigate the effectiveness of the proposed strategy comparing
its performance with the asynchronous model both in terms of quality,
efficiency and stability. Tests show that the proposed protocol does not harm
the quality of the partitioning. Moreover it is quite efficient; each
propagation step is extremely parallelizable and it is more stable than the
asynchronous model, thanks to the fact that only a small amount of
randomization is used by our proposal.
|
1103.4558
|
Representing First-Order Causal Theories by Logic Programs
|
cs.AI cs.LO
|
Nonmonotonic causal logic, introduced by Norman McCain and Hudson Turner,
became a basis for the semantics of several expressive action languages.
McCain's embedding of definite propositional causal theories into logic
programming paved the way to the use of answer set solvers for answering
queries about actions described in such languages. In this paper we extend this
embedding to nondefinite theories and to first-order causal logic.
|
1103.4578
|
Common Signal Analysis
|
cs.IT math.IT
|
A common signal is defined for any two signals which have non-zero
correlation. A mathematical method is provided to extract the best obtainable
common signal between the two signals. This analysis is extended to extracting
common signal among three signals.
|
1103.4584
|
Automatic Synthesis of Switching Controllers for Linear Hybrid Automata
|
cs.LO cs.FL cs.SY math.OC
|
In this paper we study the problem of automatically generating switching
controllers for the class of Linear Hybrid Automata, with respect to safety
objectives. We identify and solve inaccuracies contained in previous
characterizations of the problem, providing a sound and complete symbolic
fixpoint procedure, based on polyhedral abstractions of the state space. We
also prove the termination of each iteration of the procedure. Some promising
experimental results are presented, based on an implementation of the fixpoint
procedure on top of the tool PHAVer.
|
1103.4601
|
Doubly Robust Policy Evaluation and Learning
|
cs.LG cs.AI cs.RO stat.AP stat.ML
|
We study decision making in environments where the reward is only partially
observed, but can be modeled as a function of an action and an observed
context. This setting, known as contextual bandits, encompasses a wide variety
of applications including health-care policy and Internet advertising. A
central task is evaluation of a new policy given historic data consisting of
contexts, actions and received rewards. The key challenge is that the past data
typically does not faithfully represent proportions of actions taken by a new
policy. Previous approaches rely either on models of rewards or models of the
past policy. The former are plagued by a large bias whereas the latter have a
large variance.
In this work, we leverage the strength and overcome the weaknesses of the two
approaches by applying the doubly robust technique to the problems of policy
evaluation and optimization. We prove that this approach yields accurate value
estimates when we have either a good (but not necessarily consistent) model of
rewards or a good (but not necessarily consistent) model of past policy.
Extensive empirical comparison demonstrates that the doubly robust approach
uniformly improves over existing techniques, achieving both lower variance in
value estimation and better policies. As such, we expect the doubly robust
approach to become common practice.
|
1103.4659
|
Social Influencing and Associated Random Walk Models: Asymptotic
Consensus Times on the Complete Graph
|
physics.soc-ph cond-mat.stat-mech cs.SI
|
We investigate consensus formation and the asymptotic consensus times in
stylized individual- or agent-based models, in which global agreement is
achieved through pairwise negotiations with or without a bias. Considering a
class of individual-based models on finite complete graphs, we introduce a
coarse-graining approach (lumping microscopic variables into macrostates) to
analyze the ordering dynamics in an associated random-walk framework. Within
this framework, yielding a linear system, we derive general equations for the
expected consensus time and the expected time spent in each macro-state.
Further, we present the asymptotic solutions of the 2-word naming game, and
separately discuss its behavior under the influence of an external field and
with the introduction of committed agents.
|
1103.4684
|
Vector Broadcast Channels: Optimality of Threshold Feedback Policies
|
cs.IT math.IT
|
Beamforming techniques utilizing only partial channel state information (CSI)
has gained popularity over other communication strategies requiring perfect CSI
thanks to their lower feedback requirements. The amount of feedback in
beamforming based communication systems can be further reduced through
selective feedback techniques in which only the users with channels good enough
are allowed to feed back by means of a decentralized feedback policy. In this
paper, we prove that thresholding at the receiver is the rate-wise optimal
decentralized feedback policy for feedback limited systems with prescribed
feedback constraints. This result is highly adaptable due to its distribution
independent nature, provides an analytical justification for the use of
threshold feedback policies in practical systems, and reinforces previous work
analyzing threshold feedback policies as a selective feedback technique without
proving its optimality. It is robust to selfish unilateral deviations. Finally,
it reduces the search for rate-wise optimal feedback policies subject to
feedback constraints from function spaces to a finite dimensional Euclidean
space.
|
1103.4687
|
Vector Broadcast Channels: Optimal Threshold Selection Problem
|
cs.IT math.IT
|
Threshold feedback policies are well known and provably rate-wise optimal
selective feedback techniques for communication systems requiring partial
channel state information (CSI). However, optimal selection of thresholds at
mobile users to maximize information theoretic data rates subject to feedback
constraints is an open problem. In this paper, we focus on the optimal
threshold selection problem, and provide a solution for this problem for finite
feedback systems. Rather surprisingly, we show that using the same threshold
values at all mobile users is not always a rate-wise optimal feedback strategy,
even for a system with identical users experiencing statistically the same
channel conditions. By utilizing the theory of majorization, we identify an
underlying Schur-concave structure in the rate function and obtain sufficient
conditions for a homogenous threshold feedback policy to be optimal. Our
results hold for most fading channel models, and we illustrate an application
of our results to familiar Rayleigh fading channels.
|
1103.4720
|
Computer Modelling of 3D Geological Surface
|
cs.CE
|
The geological surveying presently uses methods and tools for the computer
modeling of 3D-structures of the geographical subsurface and geotechnical
characterization as well as the application of geoinformation systems for
management and analysis of spatial data, and their cartographic presentation.
The objectives of this paper are to present a 3D geological surface model of
Latur district in Maharashtra state of India. This study is undertaken through
the several processes which are discussed in this paper to generate and
visualize the automated 3D geological surface model of a projected area.
|
1103.4723
|
Automatic Extraction of Open Space Area from High Resolution Urban
Satellite Imagery
|
cs.CV
|
In the 21st century, Aerial and satellite images are information rich. They
are also complex to analyze. For GIS systems, many features require fast and
reliable extraction of open space area from high resolution satellite imagery.
In this paper we will study efficient and reliable automatic extraction
algorithm to find out the open space area from the high resolution urban
satellite imagery. This automatic extraction algorithm uses some filters and
segmentations and grouping is applying on satellite images. And the result
images may use to calculate the total available open space area and the built
up area. It may also use to compare the difference between present and past
open space area using historical urban satellite images of that same projection
|
1103.4756
|
Identification of Piecewise Linear Models of Complex Dynamical Systems
|
math.OC cs.SY
|
The paper addresses the realization and identification problem or a subclass
of piecewise-affine hybrid systems. The paper provides necessary and sufficient
conditions for existence of a realization, a characterization of minimality,
and an identification algorithm for this subclass of hybrid systems. The
considered system class and the identification problem are motivated by
applications in systems biology.
|
1103.4767
|
A comparison of Gap statistic definitions with and without logarithm
function
|
stat.ME cs.CV
|
The Gap statistic is a standard method for determining the number of clusters
in a set of data. The Gap statistic standardizes the graph of $\log(W_{k})$,
where $W_{k}$ is the within-cluster dispersion, by comparing it to its
expectation under an appropriate null reference distribution of the data. We
suggest to use $W_{k}$ instead of $\log(W_{k})$, and to compare it to the
expectation of $W_{k}$ under a null reference distribution. In fact, whenever a
number fulfills the original Gap statistic inequality, this number also
fulfills the inequality of a Gap statistic using $W_{k}$, but not \textit{vice
versa}. The two definitions of the Gap function are evaluated on several
simulated data sets and on a real data of DCE-MR images.
|
1103.4774
|
Full-Rate Full-Diversity Achieving MIMO Precoding with Partial CSIT
|
cs.IT math.IT
|
In this paper, we consider a $n_t\times n_r$ multiple-input multiple-output
(MIMO) channel subjected to block fading. Reliability (in terms of achieved
diversity order) and rate (in number of symbols transmitted per channel use)
are of interest in such channels. We propose a new precoding scheme which
achieves both full diversity ($n_tn_r$th order diversity) as well as full rate
($n_t$ symbols per channel use) using partial channel state information at the
transmitter (CSIT), applicable in MIMO systems including $n_r<n_t$ asymmetric
MIMO. The proposed scheme achieves full diversity and improved coding gain
through an optimization over the choice of constellation sets. The optimization
maximizes $d_{min}^2$ for our precoding scheme subject to an energy constraint.
The scheme requires feedback of $n_t-1$ angle parameter values, compared to
$2n_tn_r$ real coefficients in case of full CSIT. Error rate performance
results for $3\times 1$, $3\times 2$, $4\times 1$, $8\times 1$ precoded MIMO
systems (with $n_t=3,3,4,8$ symbols per channel use, respectively) show that
the proposed precoding achieves 3rd, 6th, 4th and 8th order diversities,
respectively. These performances are shown to be better than other precoding
schemes in the literature; the better performance is due to the choice of the
signal sets and the feedback angles in the proposed scheme.
|
1103.4778
|
Formal and Computational Properties of the Confidence Boost of
Association Rules
|
cs.DB cs.AI
|
Some existing notions of redundancy among association rules allow for a
logical-style characterization and lead to irredundant bases of absolutely
minimum size. One can push the intuition of redundancy further and find an
intuitive notion of interest of an association rule, in terms of its "novelty"
with respect to other rules. Namely: an irredundant rule is so because its
confidence is higher than what the rest of the rules would suggest; then, one
can ask: how much higher? We propose to measure such a sort of "novelty"
through the confidence boost of a rule, which encompasses two previous similar
notions (confidence width and rule blocking, of which the latter is closely
related to the earlier measure "improvement"). Acting as a complement to
confidence and support, the confidence boost helps to obtain small and crisp
sets of mined association rules, and solves the well-known problem that, in
certain cases, rules of negative correlation may pass the confidence bound. We
analyze the properties of two versions of the notion of confidence boost, one
of them a natural generalization of the other. We develop efficient
algorithmics to filter rules according to their confidence boost, compare the
concept to some similar notions in the bibliography, and describe the results
of some experimentation employing the new notions on standard benchmark
datasets. We describe an open-source association mining tool that embodies one
of our variants of confidence boost in such a way that the data mining process
does not require the user to select any value for any parameter.
|
1103.4784
|
Latent Capacity Region: A Case Study on Symmetric Broadcast With Common
Messages
|
cs.IT math.IT
|
We consider the problem of broadcast with common messages, and focus on the
case that the common message rate $R_{\mathcal{A}}$, i.e., the rate of the
message intended for all the receivers in the set $\mathcal{A}$, is the same
for all the set $\mathcal{A}$ of the same cardinality. Instead of attempting to
characterize the capacity region of general broadcast channels, we only
consider the structure of the capacity region that any broadcast channel should
bear. The concept of latent capacity region is useful in capturing these
underlying constraints, and we provide a complete characterization of the
latent capacity region for the symmetric broadcast problem. The converse proof
of this tight characterization relies on a deterministic broadcast channel
model. The achievability proof generalizes the familiar rate transfer argument
to include more involved erasure correction coding among messages, thus
revealing an inherent connection between broadcast with common message and
erasure correction codes.
|
1103.4787
|
Energy Management Policies for Energy-Neutral Source-Channel Coding
|
cs.IT math.IT
|
In cyber-physical systems where sensors measure the temporal evolution of a
given phenomenon of interest and radio communication takes place over short
distances, the energy spent for source acquisition and compression may be
comparable with that used for transmission. Additionally, in order to avoid
limited lifetime issues, sensors may be powered via energy harvesting and thus
collect all the energy they need from the environment. This work addresses the
problem of energy allocation over source acquisition/compression and
transmission for energy-harvesting sensors. At first, focusing on a
single-sensor, energy management policies are identified that guarantee a
maximal average distortion while at the same time ensuring the stability of the
queue connecting source and channel encoders. It is shown that the identified
class of policies is optimal in the sense that it stabilizes the queue whenever
this is feasible by any other technique that satisfies the same average
distortion constraint. Moreover, this class of policies performs an independent
resource optimization for the source and channel encoders. Analog transmission
techniques as well as suboptimal strategies that do not use the energy buffer
(battery) or use it only for adapting either source or channel encoder energy
allocation are also studied for performance comparison. The problem of
optimizing the desired trade-off between average distortion and delay is then
formulated and solved via dynamic programming tools. Finally, a system with
multiple sensors is considered and time-division scheduling strategies are
derived that are able to maintain the stability of all data queues and to meet
the average distortion constraints at all sensors whenever it is feasible.
|
1103.4820
|
Design and classification of dynamic multi-objective optimization
problems
|
cs.NE
|
In this work we provide a formal model for the different time-dependent
components that can appear in dynamic multi-objective optimization problems,
along with a classification of these components. Four main classes are
identified, corresponding to the influence of the parameters, objective
functions, previous states of the dynamic system and, last, environment
changes, which in turn lead to online optimization problems. For illustration
purposes, examples are provided for each class identified - by no means
standing as the most representative ones or exhaustive in scope.
|
1103.4854
|
When is social computation better than the sum of its parts?
|
cs.IT cs.AI math.IT
|
Social computation, whether in the form of searches performed by swarms of
agents or collective predictions of markets, often supplies remarkably good
solutions to complex problems. In many examples, individuals trying to solve a
problem locally can aggregate their information and work together to arrive at
a superior global solution. This suggests that there may be general principles
of information aggregation and coordination that can transcend particular
applications. Here we show that the general structure of this problem can be
cast in terms of information theory and derive mathematical conditions that
lead to optimal multi-agent searches. Specifically, we illustrate the problem
in terms of local search algorithms for autonomous agents looking for the
spatial location of a stochastic source. We explore the types of search
problems, defined in terms of the statistical properties of the source and the
nature of measurements at each agent, for which coordination among multiple
searchers yields an advantage beyond that gained by having the same number of
independent searchers. We show that effective coordination corresponds to
synergy and that ineffective coordination corresponds to independence as
defined using information theory. We classify explicit types of sources in
terms of their potential for synergy. We show that sources that emit
uncorrelated signals provide no opportunity for synergetic coordination while
sources that emit signals that are correlated in some way, do allow for strong
synergy between searchers. These general considerations are crucial for
designing optimal algorithms for particular search problems in real world
settings.
|
1103.4888
|
Cooperative searching for stochastic targets
|
cs.IT cs.AI math.IT
|
Spatial search problems abound in the real world, from locating hidden
nuclear or chemical sources to finding skiers after an avalanche. We exemplify
the formalism and solution for spatial searches involving two agents that may
or may not choose to share information during a search. For certain classes of
tasks, sharing information between multiple searchers makes cooperative
searching advantageous. In some examples, agents are able to realize synergy by
aggregating information and moving based on local judgments about maximal
information gathering expectations. We also explore one- and two-dimensional
simplified situations analytically and numerically to provide a framework for
analyzing more complex problems. These general considerations provide a guide
for designing optimal algorithms for real-world search problems.
|
1103.4893
|
Robust Distributed Routing in Dynamical Flow Networks - Part II: Strong
Resilience, Equilibrium Selection and Cascaded Failures
|
cs.SY math.CA math.DS math.OC nlin.AO
|
Strong resilience properties of dynamical flow networks are analyzed for
distributed routing policies. The latter are characterized by the property that
the way the inflow at a non-destination node gets split among its outgoing
links is allowed to depend only on local information about the current particle
densities on the outgoing links. The strong resilience of the network is
defined as the infimum sum of link-wise flow capacity reductions under which
the network cannot maintain the asymptotic total inflow to the destination node
to be equal to the inflow at the origin. A class of distributed routing
policies that are locally responsive to local information is shown to yield the
maximum possible strong resilience under such local information constraints for
an acyclic dynamical flow network with a single origin-destination pair. The
maximal strong resilience achievable is shown to be equal to the minimum node
residual capacity of the network. The latter depends on the limit flow of the
unperturbed network and is defined as the minimum, among all the
non-destination nodes, of the sum, over all the links outgoing from the node,
of the differences between the maximum flow capacity and the limit flow of the
unperturbed network. We propose a simple convex optimization problem to solve
for equilibrium limit flows of the unperturbed network that minimize average
delay subject to strong resilience guarantees, and discuss the use of tolls to
induce such an equilibrium limit flow in transportation networks. Finally, we
present illustrative simulations to discuss the connection between cascaded
failures and the resilience properties of the network.
|
1103.4896
|
Classification of Sets using Restricted Boltzmann Machines
|
cs.LG stat.ML
|
We consider the problem of classification when inputs correspond to sets of
vectors. This setting occurs in many problems such as the classification of
pieces of mail containing several pages, of web sites with several sections or
of images that have been pre-segmented into smaller regions. We propose
generalizations of the restricted Boltzmann machine (RBM) that are appropriate
in this context and explore how to incorporate different assumptions about the
relationship between the input sets and the target class within the RBM. In
experiments on standard multiple-instance learning datasets, we demonstrate the
competitiveness of approaches based on RBMs and apply the proposed variants to
the problem of incoming mail classification.
|
1103.4904
|
Distribution-Independent Evolvability of Linear Threshold Functions
|
cs.LG cs.CC cs.NE
|
Valiant's (2007) model of evolvability models the evolutionary process of
acquiring useful functionality as a restricted form of learning from random
examples. Linear threshold functions and their various subclasses, such as
conjunctions and decision lists, play a fundamental role in learning theory and
hence their evolvability has been the primary focus of research on Valiant's
framework (2007). One of the main open problems regarding the model is whether
conjunctions are evolvable distribution-independently (Feldman and Valiant,
2008). We show that the answer is negative. Our proof is based on a new
combinatorial parameter of a concept class that lower-bounds the complexity of
learning from correlations.
We contrast the lower bound with a proof that linear threshold functions
having a non-negligible margin on the data points are evolvable
distribution-independently via a simple mutation algorithm. Our algorithm
relies on a non-linear loss function being used to select the hypotheses
instead of 0-1 loss in Valiant's (2007) original definition. The proof of
evolvability requires that the loss function satisfies several mild conditions
that are, for example, satisfied by the quadratic loss function studied in
several other works (Michael, 2007; Feldman, 2009; Valiant, 2010). An important
property of our evolution algorithm is monotonicity, that is the algorithm
guarantees evolvability without any decreases in performance. Previously,
monotone evolvability was only shown for conjunctions with quadratic loss
(Feldman, 2009) or when the distribution on the domain is severely restricted
(Michael, 2007; Feldman, 2009; Kanade et al., 2010)
|
1103.4913
|
Automatic Open Space Area Extraction and Change Detection from High
Resolution Urban Satellite Images
|
cs.CV
|
In this paper, we study efficient and reliable automatic extraction algorithm
to find out the open space area from the high resolution urban satellite
imagery, and to detect changes from the extracted open space area during the
period 2003, 2006 and 2008. This automatic extraction and change detection
algorithm uses some filters, segmentation and grouping that are applied on
satellite images. The resultant images may be used to calculate the total
available open space area and the built up area. It may also be used to compare
the difference between present and past open space area using historical urban
satellite images of that same projection, which is an important geo spatial
data management application.
|
1103.4916
|
Detection of Spatial Changes using Spatial Data Mining
|
cs.DB
|
The Change detection based on analysis and samples are analyzed. Land
use/cover change detection based on SDM is discussed.
|
1103.4919
|
Link Prediction in Complex Networks: A Clustering Perspective
|
cs.SI physics.soc-ph
|
Link prediction is an open problem in the complex network, which attracts
much research interest currently. However, little attention has been paid to
the relation between network structure and the performance of prediction
methods. In order to fill this vital gap, we try to understand how the network
structure affects the performance of link prediction methods in the view of
clustering. Our experiments on both synthetic and real-world networks show that
as the clustering grows, the precision of these methods could be improved
remarkably, while for the sparse and weakly clustered network, they perform
poorly. We explain this through the distinguishment caused by increased
clustering between the score distribution of positive and negative instances.
Our finding also sheds light on the problem of how to select appropriate
approaches for different networks with various densities and clusterings.
|
1103.4951
|
Exact Reconstruction using Beurling Minimal Extrapolation
|
math.ST cs.IT math.IT math.OC math.PR stat.TH
|
We show that measures with finite support on the real line are the unique
solution to an algorithm, named generalized minimal extrapolation, involving
only a finite number of generalized moments (which encompass the standard
moments, the Laplace transform, the Stieltjes transformation, etc). Generalized
minimal extrapolation shares related geometric properties with basis pursuit of
Chen, Donoho and Saunders [CDS98]. Indeed we also extend some standard results
of compressed sensing (the dual polynomial, the nullspace property) to the
signed measure framework. We express exact reconstruction in terms of a simple
interpolation problem. We prove that every nonnegative measure, supported by a
set containing s points,can be exactly recovered from only 2s + 1 generalized
moments. This result leads to a new construction of deterministic sensing
matrices for compressed sensing.
|
1103.4959
|
On mean-square boundedness of stochastic linear systems with quantized
observations
|
math.OC cs.SY
|
We propose a procedure to design a state-quantizer with finitely many bins
for a marginally stable stochastic linear system evolving in $\R^d$, and a
bounded policy based on the resulting quantized state measurements to ensure
bounded second moment in closed-loop.
|
1103.4977
|
Statistical Inference for R\'enyi Entropy Functionals
|
math.ST cs.IT math.IT stat.TH
|
Numerous entropy-type characteristics (functionals) generalizing R\'enyi
entropy are widely used in mathematical statistics, physics, information
theory, and signal processing for characterizing uncertainty in probability
distributions and distribution identification problems. We consider estimators
of some entropy (integral) functionals for discrete and continuous
distributions based on the number of epsilon-close vector records in the
corresponding independent and identically distributed samples from two
distributions. The estimators form a triangular scheme of generalized
U-statistics. We show the asymptotic properties of these estimators (e.g.,
consistency and asymptotic normality). The results can be applied in various
problems in computer science and mathematical statistics (e.g., approximate
matching for random databases, record linkage, image matching).
|
1103.4979
|
An Introduction to Functional dependency in Relational Databases
|
cs.DB
|
This write-up is the suggested lecture notes for a second level course on
advanced topics in database systems for master's students of Computer Science
with a theoretical focus. A prerequisite in algorithms and an exposure to
database systems are required. Additional reading may require exposure to
mathematical logic. The starting point for these notes are from M.Y.Vardi's
survey listed herein as a reference - some of the proofs are presented as such
. This select rewrite on functional dependency is intended to provide a few
clarifications even though radically new design approaches are now being
proposed.
|
1103.5002
|
User Modeling Combining Access Logs, Page Content and Semantics
|
cs.IR cs.AI cs.HC
|
The paper proposes an approach to modeling users of large Web sites based on
combining different data sources: access logs and content of the accessed pages
are combined with semantic information about the Web pages, the users and the
accesses of the users to the Web site. The assumption is that we are dealing
with a large Web site providing content to a large number of users accessing
the site. The proposed approach represents each user by a set of features
derived from the different data sources, where some feature values may be
missing for some users. It further enables user modeling based on the provided
characteristics of the targeted user subset. The approach is evaluated on
real-world data where we compare performance of the automatic assignment of a
user to a predefined user segment when different data sources are used to
represent the users.
|
1103.5027
|
Google matrix of the world trade network
|
q-fin.GN cond-mat.stat-mech cs.SI physics.soc-ph
|
Using the United Nations Commodity Trade Statistics Database
[http://comtrade.un.org/db/] we construct the Google matrix of the world trade
network and analyze its properties for various trade commodities for all
countries and all available years from 1962 to 2009. The trade flows on this
network are classified with the help of PageRank and CheiRank algorithms
developed for the World Wide Web and other large scale directed networks. For
the world trade this ranking treats all countries on equal democratic grounds
independent of country richness. Still this method puts at the top a group of
industrially developed countries for trade in {\it all commodities}. Our study
establishes the existence of two solid state like domains of rich and poor
countries which remain stable in time, while the majority of countries are
shown to be in a gas like phase with strong rank fluctuations. A simple random
matrix model provides a good description of statistical distribution of
countries in two-dimensional rank plane. The comparison with usual ranking by
export and import highlights new features and possibilities of our approach.
|
1103.5034
|
On Understanding and Machine Understanding
|
cs.AI
|
In the present paper, we try to propose a self-similar network theory for the
basic understanding. By extending the natural languages to a kind of so called
idealy sufficient language, we can proceed a few steps to the investigation of
the language searching and the language understanding of AI.
Image understanding, and the familiarity of the brain to the surrounding
environment are also discussed. Group effects are discussed by addressing the
essense of the power of influences, and constructing the influence network of a
society. We also give a discussion of inspirations.
|
1103.5043
|
An Empirical Study of Real-World SPARQL Queries
|
cs.IR cs.AI cs.HC
|
Understanding how users tailor their SPARQL queries is crucial when designing
query evaluation engines or fine-tuning RDF stores with performance in mind. In
this paper we analyze 3 million real-world SPARQL queries extracted from logs
of the DBPedia and SWDF public endpoints. We aim at finding which are the most
used language elements both from syntactical and structural perspectives,
paying special attention to triple patterns and joins, since they are indeed
some of the most expensive SPARQL operations at evaluation phase. We have
determined that most of the queries are simple and include few triple patterns
and joins, being Subject-Subject, Subject-Object and Object-Object the most
common join types. The graph patterns are usually star-shaped and despite
triple pattern chains exist, they are generally short.
|
1103.5044
|
Mining User Comment Activity for Detecting Forum Spammers in YouTube
|
cs.IR cs.AI cs.HC
|
Research shows that comment spamming (comments which are unsolicited,
unrelated, abusive, hateful, commercial advertisements etc) in online
discussion forums has become a common phenomenon in Web 2.0 applications and
there is a strong need to counter or combat comment spamming. We present a
method to automatically detect comment spammer in YouTube (largest and a
popular video sharing website) forums. The proposed technique is based on
mining comment activity log of a user and extracting patterns (such as time
interval between subsequent comments, presence of exactly same comment across
multiple unrelated videos) indicating spam behavior. We perform empirical
analysis on data crawled from YouTube and demonstrate that the proposed method
is effective for the task of comment spammer detection.
|
1103.5046
|
From Linked Data to Relevant Data -- Time is the Essence
|
cs.IR cs.AI cs.HC
|
The Semantic Web initiative puts emphasis not primarily on putting data on
the Web, but rather on creating links in a way that both humans and machines
can explore the Web of data. When such users access the Web, they leave a trail
as Web servers maintain a history of requests. Web usage mining approaches have
been studied since the beginning of the Web given the log's huge potential for
purposes such as resource annotation, personalization, forecasting etc.
However, the impact of any such efforts has not really gone beyond generating
statistics detailing who, when, and how Web pages maintained by a Web server
were visited.
|
1103.5078
|
Algorithms for computing the greatest simulations and bisimulations
between fuzzy automata
|
cs.FL cs.AI
|
Recently, two types of simulations (forward and backward simulations) and
four types of bisimulations (forward, backward, forward-backward, and
backward-forward bisimulations) between fuzzy automata have been introduced. If
there is at least one simulation/bisimulation of some of these types between
the given fuzzy automata, it has been proved that there is the greatest
simulation/bisimulation of this kind. In the present paper, for any of the
above-mentioned types of simulations/bisimulations we provide an effective
algorithm for deciding whether there is a simulation/bisimulation of this type
between the given fuzzy automata, and for computing the greatest one, whenever
it exists. The algorithms are based on the method developed in [J.
Ignjatovi\'c, M. \'Ciri\'c, S. Bogdanovi\'c, On the greatest solutions to
certain systems of fuzzy relation inequalities and equations, Fuzzy Sets and
Systems 161 (2010) 3081-3113], which comes down to the computing of the
greatest post-fixed point, contained in a given fuzzy relation, of an isotone
function on the lattice of fuzzy relations.
|
1103.5081
|
Using Variable Threshold to Increase Capacity in a Feedback Neural
Network
|
cs.NE
|
The article presents new results on the use of variable thresholds to
increase the capacity of a feedback neural network. Non-binary networks are
also considered in this analysis.
|
1103.5110
|
Formation of Modularity in a Model of Evolving Networks
|
physics.soc-ph cs.SI nlin.AO
|
Modularity structures are common in various social and biological networks.
However, its dynamical origin remains an open question. In this work, we set up
a dynamical model describing the evolution of a social network. Based on the
observations of real social networks, we introduced a link-creating/deleting
strategy according to the local dynamics in the model. Thus the coevolution of
dynamics and topology naturally determines the network properties. It is found
that for a small coupling strength, the networked system cannot reach any
synchronization and the network topology is homogeneous. Interestingly, when
the coupling strength is large enough, the networked system spontaneously forms
communities with different dynamical states. Meanwhile, the network topology
becomes heterogeneous with modular structures. It is further shown that in a
certain parameter regime, both the degree and the community size in the formed
network follow a power-law distribution, and the networks are found to be
assortative. These results are consistent with the characteristics of many
empirical networks, and are helpful to understand the mechanism of formation of
modularity in complex networks.
|
1103.5120
|
Emergence of scale-free leadership structure in social recommender
systems
|
physics.soc-ph cs.IR cs.SI
|
The study of the organization of social networks is important for
understanding of opinion formation, rumor spreading, and the emergence of
trends and fashion. This paper reports empirical analysis of networks extracted
from four leading sites with social functionality (Delicious, Flickr, Twitter
and YouTube) and shows that they all display a scale-free leadership structure.
To reproduce this feature, we propose an adaptive network model driven by
social recommending. Artificial agent-based simulations of this model highlight
a "good get richer" mechanism where users with broad interests and good
judgments are likely to become popular leaders for the others. Simulations also
indicate that the studied social recommendation mechanism can gradually improve
the user experience by adapting to tastes of its users. Finally we outline
implications for real online resource-sharing systems.
|
1103.5128
|
Power Consumption of LDPC Decoders in Software Radio
|
cs.IT math.IT
|
LDPC code is a powerful error correcting code and has been applied to many
advanced communication systems. The prosperity of software radio has motivated
us to investigate the implementation of LDPC decoders on processors. In this
paper, we estimate and compare complexity and power consumption of LDPC
decoding algorithms running on general purpose processors. Using the estimation
results, we show two power control schemes for software radio: SNR-based
algorithm diversity and joint transmit power and receiver energy management.
Overall, this paper discusses general concerns about using processors as the
software radio platform for the implementation of LDPC decoders.
|
1103.5131
|
Analysis of Equilibria and Strategic Interaction in Complex Networks
|
cs.GT cs.SI cs.SY math.OC
|
This paper studies $n$-person simultaneous-move games with linear best
response function, where individuals interact within a given network structure.
This class of games have been used to model various settings, such as, public
goods, belief formation, peer effects, and oligopoly. The purpose of this paper
is to study the effect of the network structure on Nash equilibrium outcomes of
this class of games. Bramoull\'{e} et al. derived conditions for uniqueness and
stability of a Nash equilibrium in terms of the smallest eigenvalue of the
adjacency matrix representing the network of interactions. Motivated by this
result, we study how local structural properties of the network of interactions
affect this eigenvalue, influencing game equilibria. In particular, we use
algebraic graph theory and convex optimization to derive new bounds on the
smallest eigenvalue in terms of the distribution of degrees, cycles, and other
relevant substructures. We illustrate our results with numerical simulations
involving online social networks.
|
1103.5133
|
Cooperative Strategies for Simultaneous and Broadcast Relay Channels
|
cs.IT math.IT
|
Consider the \emph{simultaneous relay channel} (SRC) which consists of a set
of relay channels where the source wishes to transmit common and private
information to each of the destinations. This problem is recognized as being
equivalent to that of sending common and private information to several
destinations in presence of helper relays where each channel outcome becomes a
branch of the \emph{broadcast relay channel} (BRC). Cooperative schemes and
capacity region for a set with two memoryless relay channels are investigated.
The proposed coding schemes, based on \emph{Decode-and-Forward} (DF) and
\emph{Compress-and-Forward} (CF) must be capable of transmitting information
simultaneously to all destinations in such set.
Depending on the quality of source-to-relay and relay-to-destination
channels, inner bounds on the capacity of the general BRC are derived. Three
cases of particular interest are considered: cooperation is based on DF
strategy for both users --referred to as DF-DF region--, cooperation is based
on CF strategy for both users --referred to as CF-CF region--, and cooperation
is based on DF strategy for one destination and CF for the other --referred to
as DF-CF region--. These results can be seen as a generalization and hence
unification of previous works. An outer-bound on the capacity of the general
BRC is also derived. Capacity results are obtained for the specific cases of
semi-degraded and degraded Gaussian simultaneous relay channels. Rates are
evaluated for Gaussian models where the source must guarantee a minimum amount
of information to both users while additional information is sent to each of
them.
|
1103.5142
|
Asymptotic Properties of One-Bit Distributed Detection with Ordered
Transmissions
|
cs.IT cs.MA math.IT stat.AP
|
Consider a sensor network made of remote nodes connected to a common fusion
center. In a recent work Blum and Sadler [1] propose the idea of ordered
transmissions -sensors with more informative samples deliver their messages
first- and prove that optimal detection performance can be achieved using only
a subset of the total messages. Taking to one extreme this approach, we show
that just a single delivering allows making the detection errors as small as
desired, for a sufficiently large network size: a one-bit detection scheme can
be asymptotically consistent. The transmission ordering is based on the modulus
of some local statistic (MO system). We derive analytical results proving the
asymptotic consistency and, for the particular case that the local statistic is
the log-likelihood (\ell-MO system), we also obtain a bound on the error
convergence rate. All the theorems are proved under the general setup of random
number of sensors. Computer experiments corroborate the analysis and address
typical examples of applications including: non-homogeneous Poisson-deployed
networks, detection by per-sensor censoring, monitoring of energy-constrained
phenomenon.
|
1103.5163
|
Generic Controllability of 3D Swimmers in a Perfect Fluid
|
math.OC cs.SY physics.bio-ph
|
We address the problem of controlling a dynamical system governing the motion
of a 3D weighted shape changing body swimming in a perfect fluid. The rigid
displacement of the swimmer results from the exchange of momentum between
prescribed shape changes and the flow, the total impulse of the fluid-swimmer
system being constant for all times. We prove the following tracking results:
(i) Synchronized swimming: Maybe up to an arbitrarily small change of its
density, any swimmer can approximately follow any given trajectory while, in
addition, undergoing approximately any given shape changes. In this statement,
the control consists in arbitrarily small superimposed deformations; (ii)
Freestyle swimming: Maybe up to an arbitrarily small change of its density, any
swimmer can approximately tracks any given trajectory by combining suitably at
most five basic movements that can be generically chosen (no macro shape
changes are prescribed in this statement).
|
1103.5170
|
Differentially Private Spatial Decompositions
|
cs.DB
|
Differential privacy has recently emerged as the de facto standard for
private data release. This makes it possible to provide strong theoretical
guarantees on the privacy and utility of released data. While it is well-known
how to release data based on counts and simple functions under this guarantee,
it remains to provide general purpose techniques to release different kinds of
data. In this paper, we focus on spatial data such as locations and more
generally any data that can be indexed by a tree structure. Directly applying
existing differential privacy methods to this type of data simply generates
noise. Instead, we introduce a new class of "private spatial decompositions":
these adapt standard spatial indexing methods such as quadtrees and kd-trees to
provide a private description of the data distribution. Equipping such
structures with differential privacy requires several steps to ensure that they
provide meaningful privacy guarantees. Various primitives, such as choosing
splitting points and describing the distribution of points within a region,
must be done privately, and the guarantees of the different building blocks
composed to provide an overall guarantee. Consequently, we expose the design
space for private spatial decompositions, and analyze some key examples. Our
experimental study demonstrates that it is possible to build such
decompositions efficiently, and use them to answer a variety of queries
privately with high accuracy.
|
1103.5188
|
Differential Privacy: on the trade-off between Utility and Information
Leakage
|
cs.CR cs.DB cs.IT math.IT
|
Differential privacy is a notion of privacy that has become very popular in
the database community. Roughly, the idea is that a randomized query mechanism
provides sufficient privacy protection if the ratio between the probabilities
that two adjacent datasets give the same answer is bound by e^epsilon. In the
field of information flow there is a similar concern for controlling
information leakage, i.e. limiting the possibility of inferring the secret
information from the observables. In recent years, researchers have proposed to
quantify the leakage in terms of R\'enyi min mutual information, a notion
strictly related to the Bayes risk. In this paper, we show how to model the
query system in terms of an information-theoretic channel, and we compare the
notion of differential privacy with that of mutual information. We show that
differential privacy implies a bound on the mutual information (but not
vice-versa). Furthermore, we show that our bound is tight. Then, we consider
the utility of the randomization mechanism, which represents how close the
randomized answers are, in average, to the real ones. We show that the notion
of differential privacy implies a bound on utility, also tight, and we propose
a method that under certain conditions builds an optimal randomization
mechanism, i.e. a mechanism which provides the best utility while guaranteeing
differential privacy.
|
1103.5197
|
A New Secret key Agreement Scheme in a Four-Terminal Network
|
cs.CR cs.IT math.IT
|
A new scenario for generating a secret key and two private keys among three
Terminals in the presence of an external eavesdropper is considered. Terminals
1, 2 and 3 intend to share a common secret key concealed from the external
eavesdropper (Terminal 4) and simultaneously, each of Terminals 1 and 2 intends
to share a private key with Terminal 3 while keeping it concealed from each
other and from Terminal 4. All four Terminals observe i.i.d. outputs of
correlated sources and there is a public channel from Terminal 3 to Terminals 1
and 2. An inner bound of the "secret key-private keys capacity region" is
derived and the single letter capacity regions are obtained for some special
cases.
|
1103.5218
|
Generalized Symmetric Divergence Measures and the Probability of Error
|
cs.IT math.IT
|
There are three classical divergence measures exist in the literature on
information theory and statistics. These are namely, Jeffryes-Kullback-Leiber
J-divergence. Sibson-Burbea-Rao Jensen-Shannon divegernce and Taneja
Arithmetic-Geometric divergence. These three measures bear an interesting
relationship among each other. The divergence measures like Hellinger
discrimination, symmetric chi-square divergence, and triangular discrimination
are also known in the literature. In this paper, we have considered generalized
symmetric divergence measures having the measures given above as particular
cases. Bounds on the probability of error are obtained in terms of generalized
symmetric divergence measures. Study of bounds on probability of error is
extended for the difference of divergence measures.
|
1103.5219
|
Upper Bounds on the Probability of Error in terms of Mean Divergence
Measures
|
cs.IT math.IT
|
In this paper we shall consider some famous means such as arithmetic,
harmonic, geometric, root square mean, etc. Considering the difference of these
means, we can establish. some inequalities among them. Interestingly, the
difference of mean considered is convex functions. Applying some properties,
upper bounds on the probability of error are established in this paper. It is
also shown that the results obtained are sharper than obtained directly
applying known inequalities.
|
1103.5231
|
Leaders in Social Networks, the Delicious Case
|
physics.soc-ph cs.IR cs.SI
|
Finding pertinent information is not limited to search engines. Online
communities can amplify the influence of a small number of power users for the
benefit of all other users. Users' information foraging in depth and breadth
can be greatly enhanced by choosing suitable leaders. For instance in
delicious.com, users subscribe to leaders' collection which lead to a deeper
and wider reach not achievable with search engines. To consolidate such
collective search, it is essential to utilize the leadership topology and
identify influential users. Google's PageRank, as a successful search algorithm
in the World Wide Web, turns out to be less effective in networks of people. We
thus devise an adaptive and parameter-free algorithm, the LeaderRank, to
quantify user influence. We show that LeaderRank outperforms PageRank in terms
of ranking effectiveness, as well as robustness against manipulations and noisy
data. These results suggest that leaders who are aware of their clout may
reinforce the development of social networks, and thus the power of collective
search.
|
1103.5258
|
Controllability of rolling without twisting or slipping in higher
dimensions
|
math.OC cs.SY math.DG
|
We describe how the dynamical system of rolling two $n$-dimensional
connected, oriented Riemannian manifolds $M$ and $\hat M$ without twisting or
slipping, can be lifted to a nonholonomic system of elements in the product of
the oriented orthonormal frame bundles belonging to the manifolds. By
considering the lifted problem and using properties of the elements in the
respective principal Ehresmann connections, we obtain sufficient conditions for
the local controllability of the system in terms of the curvature tensors and
the sectional curvatures of the manifolds involved. We also give some results
for the particular cases when $M$ and $\hat M$ are locally symmetric or
complete.
|
1103.5269
|
Naming Games in Two-Dimensional and Small-World-Connected Random
Geometric Networks
|
cond-mat.stat-mech cs.SI physics.soc-ph
|
We investigate a prototypical agent-based model, the Naming Game, on
two-dimensional random geometric networks. The Naming Game [A. Baronchelli et
al., J. Stat. Mech.: Theory Exp. (2006) P06014.] is a minimal model, employing
local communications that captures the emergence of shared communication
schemes (languages) in a population of autonomous semiotic agents. Implementing
the Naming Games with local broadcasts on random geometric graphs, serves as a
model for agreement dynamics in large-scale, autonomously operating wireless
sensor networks. Further, it captures essential features of the scaling
properties of the agreement process for spatially-embedded autonomous agents.
Among the relevant observables capturing the temporal properties of the
agreement process, we investigate the cluster-size distribution and the
distribution of the agreement times, both exhibiting dynamic scaling. We also
present results for the case when a small density of long-range communication
links are added on top of the random geometric graph, resulting in a
"small-world"-like network and yielding a significantly reduced time to reach
global agreement. We construct a finite-size scaling analysis for the agreement
times in this case.
|
1103.5290
|
Optimal Energy Allocation for Wireless Communications with Energy
Harvesting Constraints
|
cs.IT math.IT
|
We consider the use of energy harvesters, in place of conventional batteries
with fixed energy storage, for point-to-point wireless communications. In
addition to the challenge of transmitting in a channel with time selective
fading, energy harvesters provide a perpetual but unreliable energy source. In
this paper, we consider the problem of energy allocation over a finite horizon,
taking into account channel conditions and energy sources that are time
varying, so as to maximize the throughput. Two types of side information (SI)
on the channel conditions and harvested energy are assumed to be available:
causal SI (of the past and present slots) or full SI (of the past, present and
future slots). We obtain structural results for the optimal energy allocation,
via the use of dynamic programming and convex optimization techniques. In
particular, if unlimited energy can be stored in the battery with harvested
energy and the full SI is available, we prove the optimality of a water-filling
energy allocation solution where the so-called water levels follow a staircase
function.
|
1103.5348
|
Precoding for Outage Probability Minimization on Block Fading Channels
|
cs.IT math.IT
|
The outage probability limit is a fundamental and achievable lower bound on
the word error rate of coded communication systems affected by fading. This
limit is mainly determined by two parameters: the diversity order and the
coding gain. With linear precoding, full diversity on a block fading channel
can be achieved without error-correcting code. However, the effect of precoding
on the coding gain is not well known, mainly due to the complicated expression
of the outage probability. Using a geometric approach, this paper establishes
simple upper bounds on the outage probability, the minimization of which yields
to precoding matrices that achieve very good performance. For discrete
alphabets, it is shown that the combination of constellation expansion and
precoding is sufficient to closely approach the minimum possible outage
achieved by an i.i.d. Gaussian input distribution, thus essentially maximizing
the coding gain.
|
1103.5362
|
Verhulst-Lotka-Volterra (VLV) model of ideological struggles
|
physics.soc-ph cs.SI nlin.AO
|
Let the population of e.g. a country where some opinion struggle occurs be
varying in time, according to Verhulst equation. Consider next some competition
between opinions such as the dynamics be described by Lotka and Volterra
equations. Two kinds of influences can be used, in such a model, for describing
the dynamics of an agent opinion conversion: this can occur (i) either by means
of mass communication tools, under some external field influence, or (ii) by
means of direct interactions between agents. It results, among other features,
that change(s) in environmental conditions can prevent the extinction of
populations of followers of some ideology due to different kinds of
resurrection effects. The tension arising in the country population is proposed
to be measured by an appropriately defined scale index.
|
1103.5382
|
On religion and language evolutions seen through mathematical and agent
based models
|
physics.soc-ph cs.SI nlin.AO
|
(shortened version) Religions and languages are social variables, like age,
sex, wealth or political opinions, to be studied like any other organizational
parameter. In fact, religiosity is one of the most important sociological
aspects of populations. Languages are also a characteristics of the human kind.
New religions, new languages appear though others disappear. All religions and
languages evolve when they adapt to the society developments. On the other
hand, the number of adherents of a given religion, the number of persons
speaking a language is not fixed. Several questions can be raised. E.g. from a
macroscopic point of view : How many religions/languages exist at a given time?
What is their distribution? What is their life time? How do they evolve?. From
a microscopic view point: can one invent agent based models to describe
macroscopic aspects? Does it exist simple evolution equations? It is
intuitively accepted, but also found through from statistical analysis of the
frequency distribution that an attachment process is the primary cause of the
distribution evolution : usually the initial religion/language is that of the
mother. Later on, changes can occur either due to heterogeneous agent
interaction processes or due to external field constraints, - or both. Such
cases can be illustrated with historical facts and data. It is stressed that
characteristic time scales are different, and recalled that external fields are
very relevant in the case of religions, rending the study more interesting
within a mechanistic approach
|
1103.5405
|
Network Estimation and Packet Delivery Prediction for Control over
Wireless Mesh Networks
|
cs.SY cs.NI math.OC
|
Much of the current theory of networked control systems uses simple
point-to-point communication models as an abstraction of the underlying
network. As a result, the controller has very limited information on the
network conditions and performs suboptimally. This work models the underlying
wireless multihop mesh network as a graph of links with transmission success
probabilities, and uses a recursive Bayesian estimator to provide packet
delivery predictions to the controller. The predictions are a joint probability
distribution on future packet delivery sequences, and thus capture correlations
between successive packet deliveries. We look at finite horizon LQG control
over a lossy actuation channel and a perfect sensing channel, both without
delay, to study how the controller can compensate for predicted network
outages.
|
1103.5410
|
Political protest Italian-style: The dissonance between the blogosphere
and mainstream media in the promotion and coverage of Beppe Grillo's V-day
|
cs.SI cs.CY physics.soc-ph
|
We analyze the organization, promotion and public perception of V-day, a
political rally that took place on September 8, 2007, to protest against
corruption in the Italian Parliament. Launched by blogger Beppe Grillo, and
promoted via a word of mouth mobilization on the Italian blogosphere, V-day
brought close to one million Italians in the streets on a single day, but was
mostly ignored by mainstream media. This article is divided into two parts. In
the first part, we analyze the volume and content of online articles published
by both bloggers and mainstream news sources from June 14 (the day V-day was
announced) until September 15, 2007 (one week after it took place) . We find
that the success of V-day can be attributed to the coverage of bloggers and
small-scale local news outlets only, suggesting a strong grassroots component
in the organization of the rally. We also find a dissonant thematic
relationship between content published by blogs and mainstream media: while the
majority of blogs analyzed promote V-day, major mainstream media sources
critique the methods of information production and dissemination employed by
Grillo. Based on this finding, in the second part of the study, we explore the
role of Grillo in the organization of the rally from a network analysis
perspective. We study the interlinking structure of the V-day blogosphere
network, to determine its structure, its levels of heterogeneity, and
resilience. Our analysis contradicts the hypothesis that Grillo served as a
top-down, broadcast-like source of information. Rather, we find that
information about V-day was transferred across heterogeneous nodes in a
moderately robust and resilient core network of blogs. We speculate that the
organization of V-day represents the very first case, in Italian history, of a
political demonstration developed and promoted primarily via the use of social
media on the web.
|
1103.5426
|
Interference Channels with Rate-Limited Feedback
|
cs.IT math.IT
|
We consider the two-user interference channel with rate-limited feedback.
Related prior works focus on the case where feedback links have infinite
capacity, while no research has been done for the rate-limited feedback
problem. Several new challenges arise due to the capacity limitations of the
feedback links, both in deriving inner-bounds and outer-bounds. We study this
problem under three different interference models: the El Gamal-Costa
deterministic model, the linear deterministic model, and the Gaussian model.
For the first two models, we develop an achievable scheme that employs three
techniques: Han-Kobayashi message splitting, quantize-and-binning, and
decode-and-forward. We also derive new outer-bounds for all three models and we
show the optimality of our scheme under the linear deterministic model. In the
Gaussian case, we propose a transmission strategy that incorporates lattice
codes, inspired by the ideas developed in the first two models. For symmetric
channel gains, we prove that the gap between the achievable sum-rate of the
proposed scheme and our new outer-bounds is bounded by a constant number of
bits, independent of the channel gains.
|
1103.5431
|
Identification of Nonlinear Systems with Stable Limit Cycles via Convex
Optimization
|
math.OC cs.SY
|
We propose a convex optimization procedure for black-box identification of
nonlinear state-space models for systems that exhibit stable limit cycles
(unforced periodic solutions). It extends the "robust identification error"
framework in which a convex upper bound on simulation error is optimized to fit
rational polynomial models with a strong stability guarantee. In this work, we
relax the stability constraint using the concepts of transverse dynamics and
orbital stability, thus allowing systems with autonomous oscillations to be
identified. The resulting optimization problem is convex, and can be formulated
as a semidefinite program. A simulation-error bound is proved without assuming
that the true system is in the model class, or that the number of measurements
goes to infinity. Conditions which guarantee existence of a unique limit cycle
of the model are proved and related to the model class that we search over. The
method is illustrated by identifying a high-fidelity model from experimental
recordings of a live rat hippocampal neuron in culture.
|
1103.5441
|
Nobody but You: Sensor Selection for Voltage Regulation in Smart Grid
|
cs.SY math.OC
|
The increasing availability of distributed energy resources (DERs) and
sensors in smart grid, as well as overlaying communication network, provides
substantial potential benefits for improving the power system's reliability. In
this paper, the problem of sensor selection is studied for the MAC layer design
of wireless sensor networks for regulating the voltages in smart grid. The
framework of hybrid dynamical system is proposed, using Kalman filter for
voltage state estimation and LQR feedback control for voltage adjustment. The
approach to obtain the optimal sensor selection sequence is studied. A sub-
optimal sequence is obtained by applying the sliding window algorithm.
Simulation results show that the proposed sensor selection strategy achieves a
40% performance gain over the baseline algorithm of the round-robin sensor
polling.
|
1103.5451
|
Complexity in human transportation networks: A comparative analysis of
worldwide air transportation and global cargo ship movements
|
physics.soc-ph cond-mat.stat-mech cs.SI
|
We present a comparative network theoretic analysis of the two largest global
transportation networks: The worldwide air-transportation network (WAN) and the
global cargoship network (GCSN). We show that both networks exhibit striking
statistical similarities despite significant differences in topology and
connectivity. Both networks exhibit a discontinuity in node and link
betweenness distributions which implies that these networks naturally segragate
in two different classes of nodes and links. We introduce a technique based on
effective distances, shortest paths and shortest-path trees for strongly
weighted symmetric networks and show that in a shortest-path-tree
representation the most significant features of both networks can be readily
seen. We show that effective shortest-path distance, unlike conventional
geographic distance measures, strongly correlates with node centrality
measures. Using the new technique we show that network resilience can be
investigated more precisely than with contemporary techniques that are based on
percolation theory. We extract a functional relationship between node
characteristics and resilience to network disruption. Finally we discuss the
results, their implications and conclude that dynamic processes that evolve on
both networks are expected to share universal dynamic characteristics.
|
1103.5478
|
Proof of the outage probability conjecture for MISO channels
|
cs.IT math.IT
|
In Telatar 1999, it is conjectured that the covariance matrices minimizing
the outage probability for MIMO channels with Gaussian fading are diagonal with
either zeros or constant values on the diagonal. In the MISO setting, this is
equivalent to conjecture that the Gaussian quadratic forms having largest tale
probability correspond to such diagonal matrices. We prove here the conjecture
in the MISO setting.
|
1103.5479
|
Unicity conditions for low-rank matrix recovery
|
math.NA cs.IT cs.SY math.IT math.OC math.PR
|
Low-rank matrix recovery addresses the problem of recovering an unknown
low-rank matrix from few linear measurements. Nuclear-norm minimization is a
tractible approach with a recent surge of strong theoretical backing. Analagous
to the theory of compressed sensing, these results have required random
measurements. For example, m >= Cnr Gaussian measurements are sufficient to
recover any rank-r n x n matrix with high probability. In this paper we address
the theoretical question of how many measurements are needed via any method
whatsoever --- tractible or not. We show that for a family of random
measurement ensembles, m >= 4nr - 4r^2 measurements are sufficient to guarantee
that no rank-2r matrix lies in the null space of the measurement operator with
probability one. This is a necessary and sufficient condition to ensure uniform
recovery of all rank-r matrices by rank minimization. Furthermore, this value
of $m$ precisely matches the dimension of the manifold of all rank-2r matrices.
We also prove that for a fixed rank-r matrix, m >= 2nr - r^2 + 1 random
measurements are enough to guarantee recovery using rank minimization. These
results give a benchmark to which we may compare the efficacy of nuclear-norm
minimization.
|
1103.5520
|
Shannon Entropy based Randomness Measurement and Test for Image
Encryption
|
cs.CR cs.IT math.IT
|
The quality of image encryption is commonly measured by the Shannon entropy
over the ciphertext image. However, this measurement does not consider to the
randomness of local image blocks and is inappropriate for scrambling based
image encryption methods. In this paper, a new information entropy-based
randomness measurement for image encryption is introduced which, for the first
time, answers the question of whether a given ciphertext image is sufficiently
random-like. It measures the randomness over the ciphertext in a fairer way by
calculating the averaged entropy of a series of small image blocks within the
entire test image. In order to fulfill both quantitative and qualitative
measurement, the expectation and the variance of this averaged block entropy
for a true-random image are strictly derived and corresponding numerical
reference tables are also provided. Moreover, a hypothesis test at
significance-level is given to help accept or reject the hypothesis that the
test image is ideally encrypted/random-like. Simulation results show that the
proposed test is able to give both effectively quantitative and qualitative
results for image encryption. The same idea can also be applied to measure
other digital data, like audio and video.
|
1103.5535
|
A Lattice Compress-and-Forward Scheme
|
cs.IT math.IT
|
We present a nested lattice-code-based strategy that achieves the
random-coding based Compress-and-Forward (CF) rate for the three node Gaussian
relay channel. To do so, we first outline a lattice-based strategy for the
$(X+Z_1,X+Z_2)$ Wyner-Ziv lossy source-coding with side-information problem in
Gaussian noise, a re-interpretation of the nested lattice-code-based Gaussian
Wyner-Ziv scheme presented by Zamir, Shamai, and Erez. We use the notation
$(X+Z_1,X+Z_2)$ Wyner-Ziv to mean that the source is of the form $X+ Z_1$ and
the side-information at the receiver is of the form $X+ Z_2$, for independent
Gaussian $X, Z_1$ and $Z_2$. We next use this $(X+Z_1,X+Z_2)$ Wyner-Ziv scheme
to implement a "structured" or lattice-code-based CF scheme which achieves the
classic CF rate for Gaussian relay channels. This suggests that lattice codes
may not only be useful in point-to-point single-hop source and channel coding,
in multiple access and broadcast channels, but that they may also be useful in
larger relay networks. The usage of lattice codes in larger networks is
motivated by their structured nature (possibly leading to rate gains) and
decoding (relatively simple) being more practically realizable than their
random coding based counterparts. We furthermore expect the proposed
lattice-based CF scheme to constitute a first step towards a generic structured
achievability scheme for networks such as a structured version of the recently
introduced "noisy network coding".
|
1103.5542
|
Sparsity Enhanced Decision Feedback Equalization
|
cs.IT math.IT
|
For single-carrier systems with frequency domain equalization, decision
feedback equalization (DFE) performs better than linear equalization and has
much lower computational complexity than sequence maximum likelihood detection.
The main challenge in DFE is the feedback symbol selection rule. In this paper,
we give a theoretical framework for a simple, sparsity based thresholding
algorithm. We feed back multiple symbols in each iteration, so the algorithm
converges fast and has a low computational cost. We show how the initial
solution can be obtained via convex relaxation instead of linear equalization,
and illustrate the impact that the choice of the initial solution has on the
bit error rate performance of our algorithm. The algorithm is applicable in
several existing wireless communication systems (SC-FDMA, MC-CDMA, MIMO-OFDM).
Numerical results illustrate significant performance improvement in terms of
bit error rate compared to the MMSE solution.
|
1103.5554
|
Visual Localisation of Mobile Devices in an Indoor Environment under
Network Delay Conditions
|
cs.RO
|
Current progresses in home automation and service robotic environment have
highlighted the need to develop interoperability mechanisms that allow a
standard communication between the two systems. During the development of the
DHCompliant protocol, the problem of locating mobile devices in an indoor
environment has been investigated. The communication of the device with the
location service has been carried out to study the time delay that web services
offer in front of the sockets. The importance of obtaining data from real-time
location systems portends that a basic tool for interoperability, such as web
services, can be ineffective in this scenario because of the delays added in
the invocation of services. This paper is focused on introducing a web service
to resolve a coordinates request without any significant delay in comparison
with the sockets.
|
1103.5569
|
An upper bound on community size in scalable community detection
|
physics.soc-ph cs.SI
|
It is well-known that community detection methods based on modularity
optimization often fails to discover small communities. Several objective
functions used for community detection therefore involve a resolution parameter
that allows the detection of communities at different scales. We provide an
explicit upper bound on the community size of communities resulting from the
optimization of several of these functions. We also show with a simple example
that the use of the resolution parameter may artificially force the complete
disaggregation of large and densely connected communities.
|
1103.5580
|
Designing a Miniature Wheel Arrangement for Mobile Robot Platforms
|
cs.RO
|
In this research report details of design of a miniature wheel arrangement
are presented. This miniature wheel arrangement is essentially a direction
control mechanism intended for use on a mobile robot platform or base. The
design is a specific one employing a stepper motor as actuator and as described
can only be used on a certain type of wheeled robots. However, as a basic
steering control element, more than one of these miniature wheel arrangements
can be grouped together to implement more elaborate and intelligent direction
control schemes on varying configurations of wheeled mobile robot platforms.
|
1103.5582
|
Role-similarity based comparison of directed networks
|
physics.soc-ph cs.SI q-bio.MN
|
The widespread relevance of complex networks is a valuable tool in the
analysis of a broad range of systems. There is a demand for tools which enable
the extraction of meaningful information and allow the comparison between
different systems. We present a novel measure of similarity between nodes in
different networks as a generalization of the concept of self-similarity. A
similarity matrix is assembled as the distance between feature vectors that
contain the in and out paths of all lengths for each node. Hence, nodes
operating in a similar flow environment are considered similar regardless of
network membership. We demonstrate that this method has the potential to be
influential in tasks such as assigning identity or function to uncharacterized
nodes. In addition an innovative application of graph partitioning to the raw
results extends the concept to the comparison of networks in terms of their
underlying role-structure.
|
1103.5586
|
Use of Devolved Controllers in Data Center Networks
|
cs.NI cs.SY math.OC
|
In a data center network, for example, it is quite often to use controllers
to manage resources in a centralized man- ner. Centralized control, however,
imposes a scalability problem. In this paper, we investigate the use of
multiple independent controllers instead of a single omniscient controller to
manage resources. Each controller looks after a portion of the network only,
but they together cover the whole network. This therefore solves the
scalability problem. We use flow allocation as an example to see how this
approach can manage the bandwidth use in a distributed manner. The focus is on
how to assign components of a network to the controllers so that (1) each
controller only need to look after a small part of the network but (2) there is
at least one controller that can answer any request. We outline a way to
configure the controllers to fulfill these requirements as a proof that the use
of devolved controllers is possible. We also discuss several issues related to
such implementation.
|
1103.5602
|
Time and spectral domain relative entropy: A new approach to
multivariate spectral estimation
|
math.OC cs.SY
|
The concept of spectral relative entropy rate is introduced for jointly
stationary Gaussian processes. Using classical information-theoretic results,
we establish a remarkable connection between time and spectral domain relative
entropy rates. This naturally leads to a new spectral estimation technique
where a multivariate version of the Itakura-Saito distance is employed}. It may
be viewed as an extension of the approach, called THREE, introduced by Byrnes,
Georgiou and Lindquist in 2000 which, in turn, followed in the footsteps of the
Burg-Jaynes Maximum Entropy Method. Spectral estimation is here recast in the
form of a constrained spectrum approximation problem where the distance is
equal to the processes relative entropy rate. The corresponding solution
entails a complexity upper bound which improves on the one so far available in
the multichannel framework. Indeed, it is equal to the one featured by THREE in
the scalar case. The solution is computed via a globally convergent matricial
Newton-type algorithm. Simulations suggest the effectiveness of the new
technique in tackling multivariate spectral estimation tasks, especially in the
case of short data records.
|
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