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0909.2719
|
Standards for Language Resources
|
cs.CL
|
This paper presents an abstract data model for linguistic annotations and its
implementation using XML, RDF and related standards; and to outline the work of
a newly formed committee of the International Standards Organization (ISO),
ISO/TC 37/SC 4 Language Resource Management, which will use this work as its
starting point. The primary motive for presenting the latter is to solicit the
participation of members of the research community to contribute to the work of
the committee.
|
0909.2737
|
Compressive sensing by white random convolution
|
math.OC cs.IT math.IT
|
A different compressive sensing framework, convolution with white noise
waveform followed by subsampling at fixed (not randomly selected) locations, is
studied in this paper. We show that its recoverability for sparse signals
depends on the coherence (denoted by mu) between the signal representation and
the Fourier basis. In particular, an n-dimensional signal which is S-sparse in
such a basis can be recovered with a probability exceeding 1-delta from any
fixed m~O(mu^2*S*log(n/delta)^(3/2)) output samples of the random convolution.
|
0909.2777
|
On the Symmetric Gaussian Interference Channel with Partial
Unidirectional Cooperation
|
cs.IT math.IT
|
A two-user symmetric Gaussian Interference Channel (IC) is considered in
which a noiseless unidirectional link connects one encoder to the other. Having
a constant capacity, the additional link provides partial cooperation between
the encoders. It is shown that the available cooperation can dramatically
increase the sum-capacity of the channel. This fact is proved based on
comparison of proposed lower and upper bounds on the sum-capacity. Partitioning
the data into three independent messages, namely private, common, and
cooperative ones, the transmission strategy used to obtain the lower bound
enjoys a simple type of Han-Kobayashi scheme together with a cooperative
communication scheme. A Genie-aided upper bound is developed which incorporates
the capacity of the cooperative link. Other upper bounds are based on the
sum-capacity of the Cognitive Radio Channel and cut-set bounds. For the strong
interference regime, the achievablity scheme is simplified to employ common
and/or cooperative messages but not the private one. Through a careful analysis
it is shown that the gap between these bounds is at most one and two bits per
real dimension for strong and weak interference regimes, respectively.
Moreover, the Generalized Degrees-of-Freedom of the channel is characterized.
|
0909.2817
|
Strongly Cancellative and Recovering Sets On Lattices
|
math.CO cs.IT math.IT
|
We use information theory to study recovering sets $\R_L$ and strongly
cancellative sets $\C_L$ on different lattices. These sets are special classes
of recovering pairs and cancellative sets previously discussed in [1], [3] and
[5]. We mainly focus on the lattices $B_n$ and $D_{l}^{k}$. Specifically, we
find upper bounds and constructions for the sets $\R_{B_n}$, $\C_{B_n}$, and
$\C_{D_{l}^{k}}$.
|
0909.2894
|
Adaptive Spatial Intercell Interference Cancellation in Multicell
Wireless Networks
|
cs.IT math.IT
|
Downlink spatial intercell interference cancellation (ICIC) is considered for
mitigating other-cell interference using multiple transmit antennas. A
principle question we explore is whether it is better to do ICIC or simply
standard single-cell beamforming. We explore this question analytically and
show that beamforming is preferred for all users when the edge SNR
(signal-to-noise ratio) is low ($<0$ dB), and ICIC is preferred when the edge
SNR is high ($>10$ dB), for example in an urban setting. At medium SNR, a
proposed adaptive strategy, where multiple base stations jointly select
transmission strategies based on the user location, outperforms both while
requiring a lower feedback rate than the pure ICIC approach. The employed
metric is sum rate, which is normally a dubious metric for cellular systems,
but surprisingly we show that even with this reward function the adaptive
strategy also improves fairness. When the channel information is provided by
limited feedback, the impact of the induced quantization error is also
investigated. It is shown that ICIC with well-designed feedback strategies
still provides significant throughput gain.
|
0909.2927
|
Distribution-Specific Agnostic Boosting
|
cs.LG cs.CC
|
We consider the problem of boosting the accuracy of weak learning algorithms
in the agnostic learning framework of Haussler (1992) and Kearns et al. (1992).
Known algorithms for this problem (Ben-David et al., 2001; Gavinsky, 2002;
Kalai et al., 2008) follow the same strategy as boosting algorithms in the PAC
model: the weak learner is executed on the same target function but over
different distributions on the domain. We demonstrate boosting algorithms for
the agnostic learning framework that only modify the distribution on the labels
of the points (or, equivalently, modify the target function). This allows
boosting a distribution-specific weak agnostic learner to a strong agnostic
learner with respect to the same distribution.
When applied to the weak agnostic parity learning algorithm of Goldreich and
Levin (1989) our algorithm yields a simple PAC learning algorithm for DNF and
an agnostic learning algorithm for decision trees over the uniform distribution
using membership queries. These results substantially simplify Jackson's famous
DNF learning algorithm (1994) and the recent result of Gopalan et al. (2008).
We also strengthen the connection to hard-core set constructions discovered
by Klivans and Servedio (1999) by demonstrating that hard-core set
constructions that achieve the optimal hard-core set size (given by Holenstein
(2005) and Barak et al. (2009)) imply distribution-specific agnostic boosting
algorithms. Conversely, our boosting algorithm gives a simple hard-core set
construction with an (almost) optimal hard-core set size.
|
0909.2934
|
A Convergent Online Single Time Scale Actor Critic Algorithm
|
cs.LG cs.AI
|
Actor-Critic based approaches were among the first to address reinforcement
learning in a general setting. Recently, these algorithms have gained renewed
interest due to their generality, good convergence properties, and possible
biological relevance. In this paper, we introduce an online temporal difference
based actor-critic algorithm which is proved to converge to a neighborhood of a
local maximum of the average reward. Linear function approximation is used by
the critic in order estimate the value function, and the temporal difference
signal, which is passed from the critic to the actor. The main distinguishing
feature of the present convergence proof is that both the actor and the critic
operate on a similar time scale, while in most current convergence proofs they
are required to have very different time scales in order to converge. Moreover,
the same temporal difference signal is used to update the parameters of both
the actor and the critic. A limitation of the proposed approach, compared to
results available for two time scale convergence, is that convergence is
guaranteed only to a neighborhood of an optimal value, rather to an optimal
value itself. The single time scale and identical temporal difference signal
used by the actor and the critic, may provide a step towards constructing more
biologically realistic models of reinforcement learning in the brain.
|
0909.3027
|
Language Models for Handwritten Short Message Services
|
cs.CL
|
Handwriting is an alternative method for entering texts composing Short
Message Services. However, a whole new language features the texts which are
produced. They include for instance abbreviations and other consonantal writing
which sprung up for time saving and fashion. We have collected and processed a
significant number of such handwriting SMS, and used various strategies to
tackle this challenging area of handwriting recognition. We proposed to study
more specifically three different phenomena: consonant skeleton, rebus, and
phonetic writing. For each of them, we compare the rough results produced by a
standard recognition system with those obtained when using a specific language
model.
|
0909.3028
|
Vers la reconnaissance de mini-messages manuscrits
|
cs.CL
|
Handwriting is an alternative method for entering texts which composed Short
Message Services. However, a whole new language features the texts which are
produced. They include for instance abbreviations and other consonantal writing
which sprung up for time saving and fashion. We have collected and processed a
significant number of such handwritten SMS, and used various strategies to
tackle this challenging area of handwriting recognition. We proposed to study
more specifically three different phenomena: consonant skeleton, rebus, and
phonetic writing. For each of them, we compare the rough results produced by a
standard recognition system with those obtained when using a specific language
model to take care of them.
|
0909.3055
|
Compressive Sensing Based Opportunistic Protocol for Throughput
Improvement in Wireless Networks
|
cs.IT math.IT
|
A key feature in the design of any MAC protocol is the throughput it can
provide. In wireless networks, the channel of a user is not fixed but varies
randomly. Thus, in order to maximize the throughput of the MAC protocol at any
given time, only users with large channel gains should be allowed to transmit.
In this paper, compressive sensing based opportunistic protocol for throughput
improvement in wireless networks is proposed. The protocol is based on the
traditional protocol of R-ALOHA which allows users to compete for channel
access before reserving the channel to the best user. We use compressive
sensing to find the best user, and show that the proposed protocol requires
less time for reservation and so it outperforms other schemes proposed in
literature. This makes the protocol particularly suitable for enhancing R-ALOHA
in fast fading environments. We consider both analog and digital versions of
the protocol where the channel gains sent by the user are analog and digital,
respectively.
|
0909.3123
|
Median K-flats for hybrid linear modeling with many outliers
|
cs.CV cs.LG
|
We describe the Median K-Flats (MKF) algorithm, a simple online method for
hybrid linear modeling, i.e., for approximating data by a mixture of flats.
This algorithm simultaneously partitions the data into clusters while finding
their corresponding best approximating l1 d-flats, so that the cumulative l1
error is minimized. The current implementation restricts d-flats to be
d-dimensional linear subspaces. It requires a negligible amount of storage, and
its complexity, when modeling data consisting of N points in D-dimensional
Euclidean space with K d-dimensional linear subspaces, is of order O(n K d D+n
d^2 D), where n is the number of iterations required for convergence
(empirically on the order of 10^4). Since it is an online algorithm, data can
be supplied to it incrementally and it can incrementally produce the
corresponding output. The performance of the algorithm is carefully evaluated
using synthetic and real data.
|
0909.3131
|
Constructing Linear Encoders with Good Spectra
|
cs.IT math.IT
|
Linear encoders with good joint spectra are suitable candidates for optimal
lossless joint source-channel coding (JSCC), where the joint spectrum is a
variant of the input-output complete weight distribution and is considered good
if it is close to the average joint spectrum of all linear encoders (of the
same coding rate). In spite of their existence, little is known on how to
construct such encoders in practice. This paper is devoted to their
construction. In particular, two families of linear encoders are presented and
proved to have good joint spectra. The first family is derived from Gabidulin
codes, a class of maximum-rank-distance codes. The second family is constructed
using a serial concatenation of an encoder of a low-density parity-check code
(as outer encoder) with a low-density generator matrix encoder (as inner
encoder). In addition, criteria for good linear encoders are defined for three
coding applications: lossless source coding, channel coding, and lossless JSCC.
In the framework of the code-spectrum approach, these three scenarios
correspond to the problems of constructing linear encoders with good kernel
spectra, good image spectra, and good joint spectra, respectively. Good joint
spectra imply both good kernel spectra and good image spectra, and for every
linear encoder having a good kernel (resp., image) spectrum, it is proved that
there exists a linear encoder not only with the same kernel (resp., image) but
also with a good joint spectrum. Thus a good joint spectrum is the most
important feature of a linear encoder.
|
0909.3135
|
A Random Variable Substitution Lemma With Applications to Multiple
Description Coding
|
cs.IT math.IT
|
We establish a random variable substitution lemma and use it to investigate
the role of refinement layer in multiple description coding, which clarifies
the relationship among several existing achievable multiple description
rate-distortion regions. Specifically, it is shown that the El Gamal-Cover
(EGC) region is equivalent to the EGC* region (an antecedent version of the EGC
region) while the Venkataramani-Kramer-Goyal (VKG) region (when specialized to
the 2-description case) is equivalent to the Zhang-Berger (ZB) region.
Moreover, we prove that for multiple description coding with individual and
hierarchical distortion constraints, the number of layers in the VKG scheme can
be significantly reduced when only certain weighted sum rates are concerned.
The role of refinement layer in scalable coding (a special case of multiple
description coding) is also studied.
|
0909.3146
|
An Authentication Code against Pollution Attacks in Network Coding
|
cs.IT cs.CR math.IT
|
Systems exploiting network coding to increase their throughput suffer greatly
from pollution attacks which consist of injecting malicious packets in the
network. The pollution attacks are amplified by the network coding process,
resulting in a greater damage than under traditional routing. In this paper, we
address this issue by designing an unconditionally secure authentication code
suitable for multicast network coding. The proposed scheme is robust against
pollution attacks from outsiders, as well as coalitions of malicious insiders.
Intermediate nodes can verify the integrity and origin of the packets received
without having to decode, and thus detect and discard the malicious messages
in-transit that fail the verification. This way, the pollution is canceled out
before reaching the destinations. We analyze the performance of the scheme in
terms of both multicast throughput and goodput, and show the goodput gains. We
also discuss applications to file distribution.
|
0909.3165
|
Finite-time Consensus for Nonlinear Multi-agent Systems with Fixed
Topologies
|
cs.IT cs.MA math.IT math.OC
|
In this paper, we study finite-time state consensus problems for continuous
nonlinear multi-agent systems. Building on the theory of finite-time Lyapunov
stability, we propose sufficient criteria which guarantee the system to reach a
consensus in finite time, provided that the underlying directed network
contains a spanning tree. Novel finite-time consensus protocols are introduced
as examples for applying the criteria. Simulations are also presented to
illustrate our theoretical results.
|
0909.3169
|
On Low Distortion Embeddings of Statistical Distance Measures into Low
Dimensional Spaces
|
cs.CG cs.DB
|
Statistical distance measures have found wide applicability in information
retrieval tasks that typically involve high dimensional datasets. In order to
reduce the storage space and ensure efficient performance of queries,
dimensionality reduction while preserving the inter-point similarity is highly
desirable. In this paper, we investigate various statistical distance measures
from the point of view of discovering low distortion embeddings into
low-dimensional spaces. More specifically, we consider the Mahalanobis distance
measure, the Bhattacharyya class of divergences and the Kullback-Leibler
divergence. We present a dimensionality reduction method based on the
Johnson-Lindenstrauss Lemma for the Mahalanobis measure that achieves
arbitrarily low distortion. By using the Johnson-Lindenstrauss Lemma again, we
further demonstrate that the Bhattacharyya distance admits dimensionality
reduction with arbitrarily low additive error. We also examine the question of
embeddability into metric spaces for these distance measures due to the
availability of efficient indexing schemes on metric spaces. We provide
explicit constructions of point sets under the Bhattacharyya and the
Kullback-Leibler divergences whose embeddings into any metric space incur
arbitrarily large distortions. We show that the lower bound presented for
Bhattacharyya distance is nearly tight by providing an embedding that
approaches the lower bound for relatively small dimensional datasets.
|
0909.3185
|
Construction of Additive Reed-Muller Codes
|
cs.IT math.IT
|
The well known Plotkin construction is, in the current paper, generalized and
used to yield new families of Z2Z4-additive codes, whose length, dimension as
well as minimum distance are studied. These new constructions enable us to
obtain families of Z2Z4-additive codes such that, under the Gray map, the
corresponding binary codes have the same parameters and properties as the usual
binary linear Reed-Muller codes. Moreover, the first family is the usual binary
linear Reed-Muller family.
|
0909.3226
|
Blind user detection in doubly-dispersive DS/CDMA channels
|
cs.IT math.IT
|
In this work, we consider the problem of detecting the presence of a new user
in a direct-sequence/code-division-multiple-access (DS/CDMA) system with a
doubly-dispersive fading channel, and we propose a novel blind detection
strategy which only requires knowledge of the spreading code of the user to be
detected, but no prior information as to the time-varying channel impulse
response and the structure of the multiaccess interference. The proposed
detector has a bounded constant false alarm rate (CFAR) under the design
assumptions, while providing satisfactory detection performance even in the
presence of strong cochannel interference and high user mobility.
|
0909.3257
|
The Shield that Never Was: Societies with Single-Peaked Preferences are
More Open to Manipulation and Control
|
cs.GT cs.CC cs.MA physics.soc-ph
|
Much work has been devoted, during the past twenty years, to using complexity
to protect elections from manipulation and control. Many results have been
obtained showing NP-hardness shields, and recently there has been much focus on
whether such worst-case hardness protections can be bypassed by frequently
correct heuristics or by approximations. This paper takes a very different
approach: We argue that when electorates follow the canonical political science
model of societal preferences the complexity shield never existed in the first
place. In particular, we show that for electorates having single-peaked
preferences, many existing NP-hardness results on manipulation and control
evaporate.
|
0909.3273
|
Decomposition of the NVALUE constraint
|
cs.AI
|
We study decompositions of NVALUE, a global constraint that can be used to
model a wide range of problems where values need to be counted. Whilst
decomposition typically hinders propagation, we identify one decomposition that
maintains a global view as enforcing bound consistency on the decomposition
achieves bound consistency on the original global NVALUE constraint. Such
decompositions offer the prospect for advanced solving techniques like nogood
learning and impact based branching heuristics. They may also help SAT and IP
solvers take advantage of the propagation of global constraints.
|
0909.3276
|
Symmetries of Symmetry Breaking Constraints
|
cs.AI
|
Symmetry is an important feature of many constraint programs. We show that
any symmetry acting on a set of symmetry breaking constraints can be used to
break symmetry. Different symmetries pick out different solutions in each
symmetry class. We use these observations in two methods for eliminating
symmetry from a problem. These methods are designed to have many of the
advantages of symmetry breaking methods that post static symmetry breaking
constraint without some of the disadvantages. In particular, the two methods
prune the search space using fast and efficient propagation of posted
constraints, whilst reducing the conflict between symmetry breaking and
branching heuristics. Experimental results show that the two methods perform
well on some standard benchmarks.
|
0909.3382
|
Statistical mechanical analysis of the Kronecker channel model for MIMO
wireless communication
|
cs.IT cond-mat.dis-nn cond-mat.stat-mech math.IT
|
The Kronecker channel model of wireless communication is analyzed using
statistical mechanics methods. In the model, spatial proximities among
transmission/reception antennas are taken into account as certain correlation
matrices, which generally yield non-trivial dependence among symbols to be
estimated. This prevents accurate assessment of the communication performance
by naively using a previously developed analytical scheme based on a matrix
integration formula. In order to resolve this difficulty, we develop a
formalism that can formally handle the correlations in Kronecker models based
on the known scheme. Unfortunately, direct application of the developed scheme
is, in general, practically difficult. However, the formalism is still useful,
indicating that the effect of the correlations generally increase after the
fourth order with respect to correlation strength. Therefore, the known
analytical scheme offers a good approximation in performance evaluation when
the correlation strength is sufficiently small. For a class of specific
correlation, we show that the performance analysis can be mapped to the problem
of one-dimensional spin systems in random fields, which can be investigated
without approximation by the belief propagation algorithm.
|
0909.3384
|
Comparing Single and Multiobjective Evolutionary Approaches to the
Inventory and Transportation Problem
|
cs.NE
|
EVITA, standing for Evolutionary Inventory and Transportation Algorithm, is a
two-level methodology designed to address the Inventory and Transportation
Problem (ITP) in retail chains. The top level uses an evolutionary algorithm to
obtain delivery patterns for each shop on a weekly basis so as to minimise the
inventory costs, while the bottom level solves the Vehicle Routing Problem
(VRP) for every day in order to obtain the minimum transport costs associated
to a particular set of patterns. The aim of this paper is to investigate
whether a multiobjective approach to this problem can yield any advantage over
the previously used single objective approach. The analysis performed allows us
to conclude that this is not the case and that the single objective approach is
in gene- ral preferable for the ITP in the case studied. A further conclusion
is that it is useful to employ a classical algorithm such as Clarke & Wright's
as the seed for other metaheuristics like local search or tabu search in order
to provide good results for the Vehicle Routing Problem.
|
0909.3388
|
Pattern occurrence in the dyadic expansion of square root of two and an
analysis of pseudorandom number generators
|
math.CO cs.IT math.IT
|
Recently, designs of pseudorandom number generators (PRNGs) using
integer-valued variants of logistic maps and their applications to some
cryptographic schemes have been studied, due mostly to their ease of
implementation and performance. However, it has been noted that this ease is
reduced for some choices of the PRNGs accuracy parameters. In this article, we
show that the distribution of such undesirable accuracy parameters is closely
related to the occurrence of some patterns in the dyadic expansion of the
square root of 2. We prove that for an arbitrary infinite binary word, the
asymptotic occurrence rate of these patterns is bounded in terms of the
asymptotic occurrence rate of zeroes. We also present examples of infinite
binary words that tightly achieve the bounds. As a consequence, a classical
conjecture on asymptotic evenness of occurrence of zeroes and ones in the
dyadic expansion of the square root of 2 implies that the asymptotic rate of
the undesirable accuracy parameters for the PRNGs is at least 1/6.
|
0909.3395
|
A possible low-level explanation of "temporal dynamics of brightness
induction and White's illusion"
|
cs.CV physics.bio-ph q-bio.NC
|
Based upon physiological observation on time dependent orientation
selectivity in the cells of macaque's primary visual cortex together with the
psychophysical studies on the tuning of orientation detectors in human vision
we suggest that time dependence in brightness perception can be accommodated
through the time evolution of cortical contribution to the orientation tuning
of the ODoG filter responses. A set of Difference of Gaussians functions has
been used to mimic the time dependence of orientation tuning. The tuning of
orientation preference and its inversion at a later time have been considered
in explaining qualitatively the temporal dynamics of brightness perception
observed in "Brief presentations reveal the temporal dynamics of brightness
induction and White's illusion" for 58 and 82 ms of stimulus exposure.
|
0909.3423
|
Digital Ecosystems
|
cs.MA cs.NE
|
We view Digital Ecosystems to be the digital counterparts of biological
ecosystems, which are considered to be robust, self-organising and scalable
architectures that can automatically solve complex, dynamic problems. So, this
work is concerned with the creation, investigation, and optimisation of Digital
Ecosystems, exploiting the self-organising properties of biological ecosystems.
First, we created the Digital Ecosystem, a novel optimisation technique
inspired by biological ecosystems, where the optimisation works at two levels:
a first optimisation, migration of agents which are distributed in a
decentralised peer-to-peer network, operating continuously in time; this
process feeds a second optimisation based on evolutionary computing that
operates locally on single peers and is aimed at finding solutions to satisfy
locally relevant constraints. We then investigated its self-organising aspects,
starting with an extension to the definition of Physical Complexity to include
evolving agent populations. Next, we established stability of evolving agent
populations over time, by extending the Chli-DeWilde definition of agent
stability to include evolutionary dynamics. Further, we evaluated the diversity
of the software agents within evolving agent populations. To conclude, we
considered alternative augmentations to optimise and accelerate our Digital
Ecosystem, by studying the accelerating effect of a clustering catalyst on the
evolutionary dynamics. We also studied the optimising effect of targeted
migration on the ecological dynamics, through the indirect and emergent
optimisation of the agent migration patterns. Overall, we have advanced the
understanding of creating Digital Ecosystems, the self-organisation that occurs
within them, and the optimisation of their Ecosystem-Oriented Architecture.
|
0909.3444
|
Analyse en d\'ependances \`a l'aide des grammaires d'interaction
|
cs.CL
|
This article proposes a method to extract dependency structures from
phrase-structure level parsing with Interaction Grammars. Interaction Grammars
are a formalism which expresses interactions among words using a polarity
system. Syntactical composition is led by the saturation of polarities.
Interactions take place between constituents, but as grammars are lexicalized,
these interactions can be translated at the level of words. Dependency
relations are extracted from the parsing process: every dependency is the
consequence of a polarity saturation. The dependency relations we obtain can be
seen as a refinement of the usual dependency tree. Generally speaking, this
work sheds new light on links between phrase structure and dependency parsing.
|
0909.3445
|
Grouping Synonyms by Definitions
|
cs.CL
|
We present a method for grouping the synonyms of a lemma according to its
dictionary senses. The senses are defined by a large machine readable
dictionary for French, the TLFi (Tr\'esor de la langue fran\c{c}aise
informatis\'e) and the synonyms are given by 5 synonym dictionaries (also for
French). To evaluate the proposed method, we manually constructed a gold
standard where for each (word, definition) pair and given the set of synonyms
defined for that word by the 5 synonym dictionaries, 4 lexicographers specified
the set of synonyms they judge adequate. While inter-annotator agreement ranges
on that task from 67% to at best 88% depending on the annotator pair and on the
synonym dictionary being considered, the automatic procedure we propose scores
a precision of 67% and a recall of 71%. The proposed method is compared with
related work namely, word sense disambiguation, synonym lexicon acquisition and
WordNet construction.
|
0909.3472
|
The Universal Recommender
|
cs.IR
|
We describe the Universal Recommender, a recommender system for semantic
datasets that generalizes domain-specific recommenders such as content-based,
collaborative, social, bibliographic, lexicographic, hybrid and other
recommenders. In contrast to existing recommender systems, the Universal
Recommender applies to any dataset that allows a semantic representation. We
describe the scalable three-stage architecture of the Universal Recommender and
its application to Internet Protocol Television (IPTV). To achieve good
recommendation accuracy, several novel machine learning and optimization
problems are identified. We finally give a brief argument supporting the need
for machine learning recommenders.
|
0909.3475
|
Multi-agent Coordination in Directed Moving Neighborhood Random Networks
|
cs.MA cs.IT math.IT
|
In this paper, we consider the consensus problem of dynamical multiple agents
that communicate via a directed moving neighborhood random network. Each agent
performs random walk on a weighted directed network. Agents interact with each
other through random unidirectional information flow when they coincide in the
underlying network at a given instant. For such a framework, we present
sufficient conditions for almost sure asymptotic consensus. Some existed
consensus schemes are shown to be reduced versions of the current model.
|
0909.3508
|
Compressed Sensing with Probabilistic Measurements: A Group Testing
Solution
|
cs.IT cs.DM math.IT
|
Detection of defective members of large populations has been widely studied
in the statistics community under the name "group testing", a problem which
dates back to World War II when it was suggested for syphilis screening. There
the main interest is to identify a small number of infected people among a
large population using collective samples. In viral epidemics, one way to
acquire collective samples is by sending agents inside the population. While in
classical group testing, it is assumed that the sampling procedure is fully
known to the reconstruction algorithm, in this work we assume that the decoder
possesses only partial knowledge about the sampling process. This assumption is
justified by observing the fact that in a viral sickness, there is a chance
that an agent remains healthy despite having contact with an infected person.
Therefore, the reconstruction method has to cope with two different types of
uncertainty; namely, identification of the infected population and the
partially unknown sampling procedure.
In this work, by using a natural probabilistic model for "viral infections",
we design non-adaptive sampling procedures that allow successful identification
of the infected population with overwhelming probability 1-o(1). We propose
both probabilistic and explicit design procedures that require a "small" number
of agents to single out the infected individuals. More precisely, for a
contamination probability p, the number of agents required by the probabilistic
and explicit designs for identification of up to k infected members is bounded
by m = O(k^2 (log n)/p^2) and m = O(k^2 (log n)^2 /p^2), respectively. In both
cases, a simple decoder is able to successfully identify the infected
population in time O(mn).
|
0909.3591
|
Mathematics, Recursion, and Universals in Human Languages
|
cs.CL
|
There are many scientific problems generated by the multiple and conflicting
alternative definitions of linguistic recursion and human recursive processing
that exist in the literature. The purpose of this article is to make available
to the linguistic community the standard mathematical definition of recursion
and to apply it to discuss linguistic recursion. As a byproduct, we obtain an
insight into certain "soft universals" of human languages, which are related to
cognitive constructs necessary to implement mathematical reasoning, i.e.
mathematical model theory.
|
0909.3593
|
Exploiting Unlabeled Data to Enhance Ensemble Diversity
|
cs.LG cs.AI
|
Ensemble learning aims to improve generalization ability by using multiple
base learners. It is well-known that to construct a good ensemble, the base
learners should be accurate as well as diverse. In this paper, unlabeled data
is exploited to facilitate ensemble learning by helping augment the diversity
among the base learners. Specifically, a semi-supervised ensemble method named
UDEED is proposed. Unlike existing semi-supervised ensemble methods where
error-prone pseudo-labels are estimated for unlabeled data to enlarge the
labeled data to improve accuracy, UDEED works by maximizing accuracies of base
learners on labeled data while maximizing diversity among them on unlabeled
data. Experiments show that UDEED can effectively utilize unlabeled data for
ensemble learning and is highly competitive to well-established semi-supervised
ensemble methods.
|
0909.3606
|
Extension of Path Probability Method to Approximate Inference over Time
|
cs.LG cs.CV
|
There has been a tremendous growth in publicly available digital video
footage over the past decade. This has necessitated the development of new
techniques in computer vision geared towards efficient analysis, storage and
retrieval of such data. Many mid-level computer vision tasks such as
segmentation, object detection, tracking, etc. involve an inference problem
based on the video data available. Video data has a high degree of spatial and
temporal coherence. The property must be intelligently leveraged in order to
obtain better results.
Graphical models, such as Markov Random Fields, have emerged as a powerful
tool for such inference problems. They are naturally suited for expressing the
spatial dependencies present in video data, It is however, not clear, how to
extend the existing techniques for the problem of inference over time. This
thesis explores the Path Probability Method, a variational technique in
statistical mechanics, in the context of graphical models and approximate
inference problems. It extends the method to a general framework for problems
involving inference in time, resulting in an algorithm, \emph{DynBP}. We
explore the relation of the algorithm with existing techniques, and find the
algorithm competitive with existing approaches.
The main contribution of this thesis are the extended GBP algorithm, the
extension of Path Probability Methods to the DynBP algorithm and the
relationship between them. We have also explored some applications in computer
vision involving temporal evolution with promising results.
|
0909.3609
|
Randomized Algorithms for Large scale SVMs
|
cs.LG
|
We propose a randomized algorithm for training Support vector machines(SVMs)
on large datasets. By using ideas from Random projections we show that the
combinatorial dimension of SVMs is $O({log} n)$ with high probability. This
estimate of combinatorial dimension is used to derive an iterative algorithm,
called RandSVM, which at each step calls an existing solver to train SVMs on a
randomly chosen subset of size $O({log} n)$. The algorithm has probabilistic
guarantees and is capable of training SVMs with Kernels for both classification
and regression problems. Experiments done on synthetic and real life data sets
demonstrate that the algorithm scales up existing SVM learners, without loss of
accuracy.
|
0909.3647
|
From f-divergence to quantum quasi-entropies and their use
|
cs.IT math.IT math.ST quant-ph stat.TH
|
Csiszar's f-divergence of two probability distributions was extended to the
quantum case by the author in 1985. In the quantum setting positive
semidefinite matrices are in the place of probability distributions and the
quantum generalization is called quasi-entropy which is related to some other
important concepts as covariance, quadratic costs, Fisher information,
Cramer-Rao inequality and uncertainty relation. A conjecture about the scalar
curvature of a Fisher information geometry is explained. The described subjects
are overviewed in details in the matrix setting, but at the very end the von
Neumann algebra approach is sketched shortly.
|
0909.3648
|
Random scattering of bits by prediction
|
cs.AI cs.IT math.IT
|
We investigate a population of binary mistake sequences that result from
learning with parametric models of different order. We obtain estimates of
their error, algorithmic complexity and divergence from a purely random
Bernoulli sequence. We study the relationship of these variables to the
learner's information density parameter which is defined as the ratio between
the lengths of the compressed to uncompressed files that contain the learner's
decision rule. The results indicate that good learners have a low information
density$\rho$ while bad learners have a high $\rho$. Bad learners generate
mistake sequences that are atypically complex or diverge stochastically from a
purely random Bernoulli sequence. Good learners generate typically complex
sequences with low divergence from Bernoulli sequences and they include mistake
sequences generated by the Bayes optimal predictor. Based on the static
algorithmic interference model of \cite{Ratsaby_entropy} the learner here acts
as a static structure which "scatters" the bits of an input sequence (to be
predicted) in proportion to its information density $\rho$ thereby deforming
its randomness characteristics.
|
0909.3658
|
Efficient Steganography with Provable Security Guarantees
|
cs.CR cs.IT math.IT
|
We provide a new provably-secure steganographic encryption protocol that is
proven secure in the complexity-theoretic framework of Hopper et al. The
fundamental building block of our steganographic encryption protocol is a
"one-time stegosystem" that allows two parties to transmit messages of length
shorter than the shared key with information-theoretic security guarantees. The
employment of a pseudorandom generator (PRG) permits secure transmission of
longer messages in the same way that such a generator allows the use of
one-time pad encryption for messages longer than the key in symmetric
encryption. The advantage of our construction, compared to that of Hopper et
al., is that it avoids the use of a pseudorandom function family and instead
relies (directly) on a pseudorandom generator in a way that provides linear
improvement in the number of applications of the underlying one-way permutation
per transmitted bit. This advantageous trade-off is achieved by substituting
the pseudorandom function family employed in the previous construction with an
appropriate combinatorial construction that has been used extensively in
derandomization, namely almost t-wise independent function families.
|
0909.3786
|
Kinematic calibration of Orthoglide-type mechanisms from observation of
parallel leg motions
|
cs.RO
|
The paper proposes a new calibration method for parallel manipulators that
allows efficient identification of the joint offsets using observations of the
manipulator leg parallelism with respect to the base surface. The method
employs a simple and low-cost measuring system, which evaluates deviation of
the leg location during motions that are assumed to preserve the leg
parallelism for the nominal values of the manipulator parameters. Using the
measured deviations, the developed algorithm estimates the joint offsets that
are treated as the most essential parameters to be identified. The validity of
the proposed calibration method and efficiency of the developed numerical
algorithms are confirmed by experimental results. The sensitivity of the
measurement methods and the calibration accuracy are also studied.
|
0909.3892
|
Astroinformatics: A 21st Century Approach to Astronomy
|
astro-ph.IM cs.DB cs.DL cs.IR physics.data-an
|
Data volumes from multiple sky surveys have grown from gigabytes into
terabytes during the past decade, and will grow from terabytes into tens (or
hundreds) of petabytes in the next decade. This exponential growth of new data
both enables and challenges effective astronomical research, requiring new
approaches. Thus far, astronomy has tended to address these challenges in an
informal and ad hoc manner, with the necessary special expertise being assigned
to e-Science or survey science. However, we see an even wider scope and
therefore promote a broader vision of this data-driven revolution in
astronomical research. For astronomy to effectively cope with and reap the
maximum scientific return from existing and future large sky surveys,
facilities, and data-producing projects, we need our own information science
specialists. We therefore recommend the formal creation, recognition, and
support of a major new discipline, which we call Astroinformatics.
Astroinformatics includes a set of naturally-related specialties including data
organization, data description, astronomical classification taxonomies,
astronomical concept ontologies, data mining, machine learning, visualization,
and astrostatistics. By virtue of its new stature, we propose that astronomy
now needs to integrate Astroinformatics as a formal sub-discipline within
agency funding plans, university departments, research programs, graduate
training, and undergraduate education. Now is the time for the recognition of
Astroinformatics as an essential methodology of astronomical research. The
future of astronomy depends on it.
|
0909.3895
|
The Revolution in Astronomy Education: Data Science for the Masses
|
astro-ph.IM cs.DB cs.DL cs.IR physics.ed-ph
|
As our capacity to study ever-expanding domains of our science has increased
(including the time domain, non-electromagnetic phenomena, magnetized plasmas,
and numerous sky surveys in multiple wavebands with broad spatial coverage and
unprecedented depths), so have the horizons of our understanding of the
Universe been similarly expanding. This expansion is coupled to the exponential
data deluge from multiple sky surveys, which have grown from gigabytes into
terabytes during the past decade, and will grow from terabytes into Petabytes
(even hundreds of Petabytes) in the next decade. With this increased vastness
of information, there is a growing gap between our awareness of that
information and our understanding of it. Training the next generation in the
fine art of deriving intelligent understanding from data is needed for the
success of sciences, communities, projects, agencies, businesses, and
economies. This is true for both specialists (scientists) and non-specialists
(everyone else: the public, educators and students, workforce). Specialists
must learn and apply new data science research techniques in order to advance
our understanding of the Universe. Non-specialists require information literacy
skills as productive members of the 21st century workforce, integrating
foundational skills for lifelong learning in a world increasingly dominated by
data. We address the impact of the emerging discipline of data science on
astronomy education within two contexts: formal education and lifelong
learners.
|
0909.3911
|
A Method for Extraction and Recognition of Isolated License Plate
Characters
|
cs.CV
|
A method to extract and recognize isolated characters in license plates is
proposed. In extraction stage, the proposed method detects isolated characters
by using Difference-of-Gaussian (DOG) function, The DOG function, similar to
Laplacian of Gaussian function, was proven to produce the most stable image
features compared to a range of other possible image functions. The candidate
characters are extracted by doing connected component analysis on different
scale DOG images. In recognition stage, a novel feature vector named
accumulated gradient projection vector (AGPV) is used to compare the candidate
character with the standard ones. The AGPV is calculated by first projecting
pixels of similar gradient orientations onto specific axes, and then
accumulates the projected gradient magnitudes by each axis. In the experiments,
the AGPVs are proven to be invariant from image scaling and rotation, and
robust to noise and illumination change.
|
0909.3917
|
Stiffness Analysis Of Multi-Chain Parallel Robotic Systems
|
cs.RO
|
The paper presents a new stiffness modelling method for multi-chain parallel
robotic manipulators with flexible links and compliant actuating joints. In
contrast to other works, the method involves a FEA-based link stiffness
evaluation and employs a new solution strategy of the kinetostatic equations,
which allows computing the stiffness matrix for singular postures and to take
into account influence of the external forces. The advantages of the developed
technique are confirmed by application examples, which deal with stiffness
analysis of a parallel manipulator of the Orthoglide family
|
0909.3966
|
Robust THP Transceiver Designs for Multiuser MIMO Downlink with
Imperfect CSIT
|
cs.IT math.IT
|
In this paper, we present robust joint non-linear transceiver designs for
multiuser multiple-input multiple-output (MIMO) downlink in the presence of
imperfections in the channel state information at the transmitter (CSIT). The
base station (BS) is equipped with multiple transmit antennas, and each user
terminal is equipped with one or more receive antennas. The BS employs
Tomlinson-Harashima precoding (THP) for inter-user interference
pre-cancellation at the transmitter. We consider robust transceiver designs
that jointly optimize the transmit THP filters and receive filter for two
models of CSIT errors. The first model is a stochastic error (SE) model, where
the CSIT error is Gaussian-distributed. This model is applicable when the CSIT
error is dominated by channel estimation error. In this case, the proposed
robust transceiver design seeks to minimize a stochastic function of the sum
mean square error (SMSE) under a constraint on the total BS transmit power. We
propose an iterative algorithm to solve this problem. The other model we
consider is a norm-bounded error (NBE) model, where the CSIT error can be
specified by an uncertainty set. This model is applicable when the CSIT error
is dominated by quantization errors. In this case, we consider a worst-case
design. For this model, we consider robust i) minimum SMSE, ii)
MSE-constrained, and iii) MSE-balancing transceiver designs. We propose
iterative algorithms to solve these problems, wherein each iteration involves a
pair of semi-definite programs (SDP). Further, we consider an extension of the
proposed algorithm to the case with per-antenna power constraints.
|
0909.4017
|
On Degrees of Freedom Region of MIMO Networks without CSIT
|
cs.IT math.IT
|
In this paper, we study the effect of the absence of channel knowledge for
multiple-input-multiple-output (MIMO) networks. Specifically, we assume perfect
channel state information at the receivers, no channel state information at the
transmitter(s), and independent identically distributed (i.i.d.) Rayleigh
fading across antennas, users and time slots. We provide the characterization
of the degrees of freedom (DoF) region for a 2-user MIMO broadcast channel. We
then provide a DoF region outer bound for a 2-user MIMO interference channel.
This bound is shown to be tight for all possible combinations of the number of
antennas at each node except for one case. As a byproduct of this analysis we
point out the potential of interference alignment in the 2-user MIMO
interference channel with no CSIT.
|
0909.4126
|
On an Inequality of Karlin and Rinott Concerning Weighted Sums of i.i.d.
Random Variables
|
cs.IT math.IT math.PR
|
We present an entropy comparison result concerning weighted sums of
independent and identically distributed random variables.
|
0909.4177
|
On the Degrees of Freedom of Finite State Compound Wireless Networks -
Settling a Conjecture by Weingarten et. al
|
cs.IT math.IT
|
We explore the degrees of freedom (DoF) of three classes of finite state
compound wireless networks in this paper. First, we study the multiple-input
single-output (MISO) finite state compound broadcast channel (BC) with
arbitrary number of users and antennas at the transmitter. In prior work,
Weingarten et. al. have found inner and outer bounds on the DoF with 2 users.
The bounds have a different character. While the inner bound collapses to unity
as the number of states increases, the outer bound does not diminish with the
increasing number of states beyond a threshold value. It has been conjectured
that the outer bound is loose and the inner bound represents the actual DoF. In
the complex setting (all signals, noise, and channel coefficients are complex
variables) we solve a few cases to find that the outer bound -and not the inner
bound- of Weingarten et. al. is tight. For the real setting (all signals, noise
and channel coefficients are real variables) we completely characterize the
DoF, once again proving that the outer bound of Weingarten et. al. is tight. We
also extend the results to arbitrary number of users. Second, we characterize
the DoF of finite state scalar (single antenna nodes) compound X networks with
arbitrary number of users in the real setting. Third, we characterize the DoF
of finite state scalar compound interference networks with arbitrary number of
users in both the real and complex setting. The key finding is that scalar
interference networks and (real) X networks do not lose any DoF due to channel
uncertainty at the transmitter in the finite state compound setting. The finite
state compound MISO BC does lose DoF relative to the perfect CSIT scenario.
However, what is lost is only the DoF benefit of joint processing at transmit
antennas, without which the MISO BC reduces to an X network.
|
0909.4196
|
Personal Information Databases
|
cs.DB
|
One of the most important aspects of security organization is to establish a
framework to identify security significant points where policies and procedures
are declared. The (information) security infrastructure comprises entities,
processes, and technology. All are participants in handling information, which
is the item that needs to be protected. Privacy and security information
technology is a critical and unmet need in the management of personal
information. This paper proposes concepts and technologies for management of
personal information. Two different types of information can be distinguished:
personal information and nonpersonal information. Personal information can be
either personal identifiable information (PII), or nonidentifiable information
(NII). Security, policy, and technical requirements can be based on this
distinction. At the conceptual level, PII is defined and formalized by
propositions over infons (discrete pieces of information) that specify
transformations in PII and NII. PII is categorized into simple infons that
reflect the proprietor s aspects, relationships with objects, and relationships
with other proprietors. The proprietor is the identified person about whom the
information is communicated. The paper proposes a database organization that
focuses on the PII spheres of proprietors. At the design level, the paper
describes databases of personal identifiable information built exclusively for
this type of information, with their own conceptual scheme, system management,
and physical structure.
|
0909.4203
|
Error Exponents for the Gaussian Channel with Active Noisy Feedback
|
cs.IT math.IT
|
We study the best exponential decay in the blocklength of the probability of
error that can be achieved in the transmission of a single bit over the
Gaussian channel with an active noisy Gaussian feedback link. We impose an
\emph{expected} block power constraint on the forward link and study both
\emph{almost-sure} and \emph{expected} block power constraints on the feedback
link. In both cases the best achievable error exponents are finite and grow
approximately proportionally to the larger between the signal-to-noise ratios
on the forward and feedback links. The error exponents under almost-sure block
power constraints are typically strictly smaller than under expected
constraints. Some of the results extend to communication at arbitrary rates
below capacity and to general discrete memoryless channels.
|
0909.4233
|
On the optimality of universal classifiers for finite-length individual
test sequences
|
cs.IT math.IT
|
We consider pairs of finite-length individual sequences that are realizations
of unknown, finite alphabet, stationary sources in a clas M of sources with
vanishing memory (e.g. stationary Markov sources).
The task of a universal classifier is to decide whether the two sequences are
emerging from the same source or are emerging from two distinct sources in M,
and it has to carry this task without any prior knowledge of the two underlying
probability measures.
Given a fidelity function and a fidelity criterion, the probability of
classification error for a given universal classifier is defined.
Two universal classifiers are defined for pairs of $N$ -sequence: A
"classical" fixed-length (FL) universal classifier and an alternative
variable-length (VL) universal classifier.
Following Wyner and Ziv (1996) it is demonstrated that if the length of the
individual sequences N is smaller than a cut-off value that is determined by
the properties of the class M, any universal classifier will fail with high
probability .
It is demonstrated that for values of N larger than the cut-off rate, the
classification error relative to either one of the two classifiers tends to
zero as the length of the sequences tends to infinity.
However, the probability of classification error that is associated with the
variable-length universal classifier is uniformly smaller (or equal) to the one
that is associated with the "classical" fixed-length universal classifier, for
any finite length.
|
0909.4280
|
Towards Multimodal Content Representation
|
cs.CL
|
Multimodal interfaces, combining the use of speech, graphics, gestures, and
facial expressions in input and output, promise to provide new possibilities to
deal with information in more effective and efficient ways, supporting for
instance: - the understanding of possibly imprecise, partial or ambiguous
multimodal input; - the generation of coordinated, cohesive, and coherent
multimodal presentations; - the management of multimodal interaction (e.g.,
task completion, adapting the interface, error prevention) by representing and
exploiting models of the user, the domain, the task, the interactive context,
and the media (e.g. text, audio, video). The present document is intended to
support the discussion on multimodal content representation, its possible
objectives and basic constraints, and how the definition of a generic
representation framework for multimodal content representation may be
approached. It takes into account the results of the Dagstuhl workshop, in
particular those of the informal working group on multimodal meaning
representation that was active during the workshop (see
http://www.dfki.de/~wahlster/Dagstuhl_Multi_Modality, Working Group 4).
|
0909.4349
|
Leader-following Consensus Problems with a Time-varying Leader under
Measurement Noises
|
cs.MA cs.IT math.IT
|
In this paper, we consider a leader-following consensus problem for networks
of continuous-time integrator agents with a time-varying leader under
measurement noises. We propose a neighbor-based state-estimation protocol for
every agent to track the leader, and time-varying consensus gains are
introduced to attenuate the noises. By combining the tools of stochastic
analysis and algebraic graph theory, we study mean square convergence of this
multi-agent system under directed fixed as well as switching interconnection
topologies. Sufficient conditions are given for mean square consensus in both
cases. Finally, a numerical example is given to illustrate our theoretical
results.
|
0909.4359
|
Sparse Signal Reconstruction via Iterative Support Detection
|
cs.IT math.IT math.NA math.OC
|
We present a novel sparse signal reconstruction method "ISD", aiming to
achieve fast reconstruction and a reduced requirement on the number of
measurements compared to the classical l_1 minimization approach. ISD addresses
failed reconstructions of l_1 minimization due to insufficient measurements. It
estimates a support set I from a current reconstruction and obtains a new
reconstruction by solving the minimization problem \min{\sum_{i\not\in
I}|x_i|:Ax=b}, and it iterates these two steps for a small number of times. ISD
differs from the orthogonal matching pursuit (OMP) method, as well as its
variants, because (i) the index set I in ISD is not necessarily nested or
increasing and (ii) the minimization problem above updates all the components
of x at the same time. We generalize the Null Space Property to Truncated Null
Space Property and present our analysis of ISD based on the latter.
We introduce an efficient implementation of ISD, called threshold--ISD, for
recovering signals with fast decaying distributions of nonzeros from
compressive sensing measurements. Numerical experiments show that
threshold--ISD has significant advantages over the classical l_1 minimization
approach, as well as two state--of--the--art algorithms: the iterative
reweighted l_1 minimization algorithm (IRL1) and the iterative reweighted
least--squares algorithm (IRLS).
MATLAB code is available for download from
http://www.caam.rice.edu/~optimization/L1/ISD/.
|
0909.4385
|
The meta book and size-dependent properties of written language
|
physics.soc-ph cs.CL physics.data-an
|
Evidence is given for a systematic text-length dependence of the power-law
index gamma of a single book. The estimated gamma values are consistent with a
monotonic decrease from 2 to 1 with increasing length of a text. A direct
connection to an extended Heap's law is explored. The infinite book limit is,
as a consequence, proposed to be given by gamma = 1 instead of the value
gamma=2 expected if the Zipf's law was ubiquitously applicable. In addition we
explore the idea that the systematic text-length dependence can be described by
a meta book concept, which is an abstract representation reflecting the
word-frequency structure of a text. According to this concept the
word-frequency distribution of a text, with a certain length written by a
single author, has the same characteristics as a text of the same length pulled
out from an imaginary complete infinite corpus written by the same author.
|
0909.4409
|
Clustering with Obstacles in Spatial Databases
|
cs.DB
|
Clustering large spatial databases is an important problem, which tries to
find the densely populated regions in a spatial area to be used in data mining,
knowledge discovery, or efficient information retrieval. However most
algorithms have ignored the fact that physical obstacles such as rivers, lakes,
and highways exist in the real world and could thus affect the result of the
clustering. In this paper, we propose CPO, an efficient clustering technique to
solve the problem of clustering in the presence of obstacles. The proposed
algorithm divides the spatial area into rectangular cells. Each cell is
associated with statistical information used to label the cell as dense or
non-dense. It also labels each cell as obstructed (i.e. intersects any
obstacle) or nonobstructed. For each obstructed cell, the algorithm finds a
number of non-obstructed sub-cells. Then it finds the dense regions of
non-obstructed cells or sub-cells by a breadthfirst search as the required
clusters with a center to each region.
|
0909.4412
|
Algorithm for Spatial Clustering with Obstacles
|
cs.DB
|
In this paper, we propose an efficient clustering technique to solve the
problem of clustering in the presence of obstacles. The proposed algorithm
divides the spatial area into rectangular cells. Each cell is associated with
statistical information that enables us to label the cell as dense or
non-dense. We also label each cell as obstructed (i.e. intersects any obstacle)
or non-obstructed. Then the algorithm finds the regions (clusters) of
connected, dense, non-obstructed cells. Finally, the algorithm finds a center
for each such region and returns those centers as centers of the relatively
dense regions (clusters) in the spatial area.
|
0909.4416
|
A baseline for content-based blog classification
|
cs.IR
|
A content-based network representation of web logs (blogs) using a basic
word-overlap similarity measure is presented. Due to a strong signal in blog
data the approach is sufficient for accurately classifying blogs. Using Swedish
blog data we demonstrate that blogs that treat similar subjects are organized
in clusters that, in turn, are hierarchically organized in higher-order
clusters. The simplicity of the representation renders it both computationally
tractable and transparent. We therefore argue that the approach is suitable as
a baseline when developing and analyzing more advanced content-based
representations of the blogosphere.
|
0909.4437
|
Manipulation and gender neutrality in stable marriage procedures
|
cs.AI cs.GT
|
The stable marriage problem is a well-known problem of matching men to women
so that no man and woman who are not married to each other both prefer each
other. Such a problem has a wide variety of practical applications ranging from
matching resident doctors to hospitals to matching students to schools. A
well-known algorithm to solve this problem is the Gale-Shapley algorithm, which
runs in polynomial time.
It has been proven that stable marriage procedures can always be manipulated.
Whilst the Gale-Shapley algorithm is computationally easy to manipulate, we
prove that there exist stable marriage procedures which are NP-hard to
manipulate. We also consider the relationship between voting theory and stable
marriage procedures, showing that voting rules which are NP-hard to manipulate
can be used to define stable marriage procedures which are themselves NP-hard
to manipulate. Finally, we consider the issue that stable marriage procedures
like Gale-Shapley favour one gender over the other, and we show how to use
voting rules to make any stable marriage procedure gender neutral.
|
0909.4441
|
Dealing with incomplete agents' preferences and an uncertain agenda in
group decision making via sequential majority voting
|
cs.AI cs.GT cs.MA
|
We consider multi-agent systems where agents' preferences are aggregated via
sequential majority voting: each decision is taken by performing a sequence of
pairwise comparisons where each comparison is a weighted majority vote among
the agents. Incompleteness in the agents' preferences is common in many
real-life settings due to privacy issues or an ongoing elicitation process. In
addition, there may be uncertainty about how the preferences are aggregated.
For example, the agenda (a tree whose leaves are labelled with the decisions
being compared) may not yet be known or fixed. We therefore study how to
determine collectively optimal decisions (also called winners) when preferences
may be incomplete, and when the agenda may be uncertain. We show that it is
computationally easy to determine if a candidate decision always wins, or may
win, whatever the agenda. On the other hand, it is computationally hard to know
wheth er a candidate decision wins in at least one agenda for at least one
completion of the agents' preferences. These results hold even if the agenda
must be balanced so that each candidate decision faces the same number of
majority votes. Such results are useful for reasoning about preference
elicitation. They help understand the complexity of tasks such as determining
if a decision can be taken collectively, as well as knowing if the winner can
be manipulated by appropriately ordering the agenda.
|
0909.4446
|
Elicitation strategies for fuzzy constraint problems with missing
preferences: algorithms and experimental studies
|
cs.AI
|
Fuzzy constraints are a popular approach to handle preferences and
over-constrained problems in scenarios where one needs to be cautious, such as
in medical or space applications. We consider here fuzzy constraint problems
where some of the preferences may be missing. This models, for example,
settings where agents are distributed and have privacy issues, or where there
is an ongoing preference elicitation process. In this setting, we study how to
find a solution which is optimal irrespective of the missing preferences. In
the process of finding such a solution, we may elicit preferences from the user
if necessary. However, our goal is to ask the user as little as possible. We
define a combined solving and preference elicitation scheme with a large number
of different instantiations, each corresponding to a concrete algorithm which
we compare experimentally. We compute both the number of elicited preferences
and the "user effort", which may be larger, as it contains all the preference
values the user has to compute to be able to respond to the elicitation
requests. While the number of elicited preferences is important when the
concern is to communicate as little information as possible, the user effort
measures also the hidden work the user has to do to be able to communicate the
elicited preferences. Our experimental results show that some of our algorithms
are very good at finding a necessarily optimal solution while asking the user
for only a very small fraction of the missing preferences. The user effort is
also very small for the best algorithms. Finally, we test these algorithms on
hard constraint problems with possibly missing constraints, where the aim is to
find feasible solutions irrespective of the missing constraints.
|
0909.4452
|
Flow-Based Propagators for the SEQUENCE and Related Global Constraints
|
cs.AI
|
We propose new filtering algorithms for the SEQUENCE constraint and some
extensions of the SEQUENCE constraint based on network flows. We enforce domain
consistency on the SEQUENCE constraint in $O(n^2)$ time down a branch of the
search tree. This improves upon the best existing domain consistency algorithm
by a factor of $O(\log n)$. The flows used in these algorithms are derived from
a linear program. Some of them differ from the flows used to propagate global
constraints like GCC since the domains of the variables are encoded as costs on
the edges rather than capacities. Such flows are efficient for maintaining
bounds consistency over large domains and may be useful for other global
constraints.
|
0909.4456
|
The Weighted CFG Constraint
|
cs.AI
|
We introduce the weighted CFG constraint and propose a propagation algorithm
that enforces domain consistency in $O(n^3|G|)$ time. We show that this
algorithm can be decomposed into a set of primitive arithmetic constraints
without hindering propagation.
|
0909.4474
|
Reconstruction of the equilibrium of the plasma in a Tokamak and
identification of the current density profile in real time
|
math.NA cs.SY math.AP math.OC
|
The reconstruction of the equilibrium of a plasma in a Tokamak is a free
boundary problem described by the Grad-Shafranov equation in axisymmetric
configuration. The right-hand side of this equation is a nonlinear source,
which represents the toroidal component of the plasma current density. This
paper deals with the identification of this nonlinearity source from
experimental measurements in real time. The proposed method is based on a fixed
point algorithm, a finite element resolution, a reduced basis method and a
least-square optimization formulation. This is implemented in a software called
Equinox with which several numerical experiments are conducted to explore the
identification problem. It is shown that the identification of the profile of
the averaged current density and of the safety factor as a function of the
poloidal flux is very robust.
|
0909.4484
|
Error exponents for Neyman-Pearson detection of a continuous-time
Gaussian Markov process from noisy irregular samples
|
cs.IT math.IT
|
This paper addresses the detection of a stochastic process in noise from
irregular samples. We consider two hypotheses. The \emph{noise only} hypothesis
amounts to model the observations as a sample of a i.i.d. Gaussian random
variables (noise only). The \emph{signal plus noise} hypothesis models the
observations as the samples of a continuous time stationary Gaussian process
(the signal) taken at known but random time-instants corrupted with an additive
noise. Two binary tests are considered, depending on which assumptions is
retained as the null hypothesis. Assuming that the signal is a linear
combination of the solution of a multidimensional stochastic differential
equation (SDE), it is shown that the minimum Type II error probability
decreases exponentially in the number of samples when the False Alarm
probability is fixed. This behavior is described by \emph{error exponents} that
are completely characterized. It turns out that they are related with the
asymptotic behavior of the Kalman Filter in random stationary environment,
which is studied in this paper. Finally, numerical illustrations of our claims
are provided in the context of sensor networks.
|
0909.4573
|
Efficient Linear Precoding in Downlink Cooperative Cellular Networks
with Soft Interference Nulling
|
cs.IT math.IT
|
A simple line network model is proposed to study the downlink cellular
network. Without base station cooperation, the system is interference-limited.
The interference limitation is overcome when the base stations are allowed to
jointly encode the user signals, but the capacity-achieving dirty paper coding
scheme can be too complex for practical implementation. A new linear precoding
technique called soft interference nulling (SIN) is proposed, which performs at
least as well as zero-forcing (ZF) beamforming under full network coordination.
Unlike ZF, SIN allows the possibility of but over-penalizes interference. The
SIN precoder is computed by solving a convex optimization problem, and the
formulation is extended to multiple-antenna channels. SIN can be applied when
only a limited number of base stations cooperate; it is shown that SIN under
partial network coordination can outperform full network coordination ZF at
moderate SNRs.
|
0909.4575
|
Randomness Efficient Steganography
|
cs.CR cs.IT math.IT
|
Steganographic protocols enable one to embed covert messages into
inconspicuous data over a public communication channel in such a way that no
one, aside from the sender and the intended receiver, can even detect the
presence of the secret message. In this paper, we provide a new
provably-secure, private-key steganographic encryption protocol secure in the
framework of Hopper et al. We first present a "one-time stegosystem" that
allows two parties to transmit messages of length at most that of the shared
key with information-theoretic security guarantees. The employment of a
pseudorandom generator (PRG) permits secure transmission of longer messages in
the same way that such a generator allows the use of one-time pad encryption
for messages longer than the key in symmetric encryption. The advantage of our
construction, compared to all previous work is randomness efficiency: in the
information theoretic setting our protocol embeds a message of length n bits
using a shared secret key of length (1+o(1))n bits while achieving security
2^{-n/log^{O(1)}n}; simply put this gives a rate of key over message that is 1
as n tends to infinity (the previous best result achieved a constant rate
greater than 1 regardless of the security offered). In this sense, our protocol
is the first truly randomness efficient steganographic system. Furthermore, in
our protocol, we can permit a portion of the shared secret key to be public
while retaining precisely n private key bits. In this setting, by separating
the public and the private randomness of the shared key, we achieve security of
2^{-n}. Our result comes as an effect of the application of randomness
extractors to stegosystem design. To the best of our knowledge this is the
first time extractors have been applied in steganography.
|
0909.4588
|
Discrete MDL Predicts in Total Variation
|
math.PR cs.IT cs.LG math.IT math.ST stat.ML stat.TH
|
The Minimum Description Length (MDL) principle selects the model that has the
shortest code for data plus model. We show that for a countable class of
models, MDL predictions are close to the true distribution in a strong sense.
The result is completely general. No independence, ergodicity, stationarity,
identifiability, or other assumption on the model class need to be made. More
formally, we show that for any countable class of models, the distributions
selected by MDL (or MAP) asymptotically predict (merge with) the true measure
in the class in total variation distance. Implications for non-i.i.d. domains
like time-series forecasting, discriminative learning, and reinforcement
learning are discussed.
|
0909.4589
|
Cross-correlation properties of cyclotomic sequences
|
cs.IT cs.DM math.CO math.IT
|
Sequences with good correlation properties are widely used in engineering
applications, especially in the area of communications. Among the known
sequences, cyclotomic families have the optimal autocorrelation property. In
this paper, we decide the cross-correlation function of the known cyclotomic
sequences completely. Moreover, to get our results, the relations between the
multiplier group and the decimations of the characteristic sequence are also
established for an arbitrary difference set.
|
0909.4592
|
Autocorrelation-Run Formula for Binary Sequences
|
cs.IT cs.DM math.CO math.IT
|
The autocorrelation function and the run structure are two basic notions for
binary sequences, and have been used as two independent postulates to test
randomness of binary sequences ever since Golomb 1955. In this paper, we prove
for binary sequence that the autocorrelation function is in fact completely
determined by its run structure.
|
0909.4601
|
Rank Metric Decoder Architectures for Random Linear Network Coding with
Error Control
|
cs.IT math.IT
|
While random linear network coding is a powerful tool for disseminating
information in communication networks, it is highly susceptible to errors
caused by various sources. Due to error propagation, errors greatly deteriorate
the throughput of network coding and seriously undermine both reliability and
security of data. Hence error control for network coding is vital. Recently,
constant-dimension codes (CDCs), especially K\"otter-Kschischang (KK) codes,
have been proposed for error control in random linear network coding. KK codes
can also be constructed from Gabidulin codes, an important class of rank metric
codes. Rank metric decoders have been recently proposed for both Gabidulin and
KK codes, but they have high computational complexities. Furthermore, it is not
clear whether such decoders are feasible and suitable for hardware
implementations. In this paper, we reduce the complexities of rank metric
decoders and propose novel decoder architectures for both codes. The synthesis
results of our decoder architectures for Gabidulin and KK codes with limited
error-correcting capabilities over small fields show that our architectures not
only are affordable, but also achieve high throughput.
|
0909.4603
|
Scalable Inference for Latent Dirichlet Allocation
|
cs.LG
|
We investigate the problem of learning a topic model - the well-known Latent
Dirichlet Allocation - in a distributed manner, using a cluster of C processors
and dividing the corpus to be learned equally among them. We propose a simple
approximated method that can be tuned, trading speed for accuracy according to
the task at hand. Our approach is asynchronous, and therefore suitable for
clusters of heterogenous machines.
|
0909.4604
|
Interference Alignment for the $K$ User MIMO Interference Channel
|
cs.IT math.IT
|
We consider the $K$-user Multiple Input Multiple Output (MIMO) Gaussian
interference channel with $M$ antennas at each transmitter and $N$ antennas at
each receiver. It is assumed that channel coefficients are constant and are
available at all transmitters and at all receivers. The main objective of this
paper is to characterize the Degrees of Freedom (DoF) for this channel. Using a
new interference alignment technique which has been recently introduced in
\cite{abolfazl-final}, we show that $\frac{MN}{M+N} K$ degrees of freedom can
be achieved for almost all channel realizations. Also, a new upper-bound on the
DoF of this channel is provided. This upper-bound coincides with our achievable
DoF for $K\geq K_u\define\frac{M+N}{\gcd(M,N)}$, where $\gcd(M,N)$ denotes the
greatest common divisor of $M$ and $N$. This gives an exact characterization of
DoF for $M\times N$ MIMO Gaussian interference channel in the case of $K\geq
K_u$.
|
0909.4767
|
Semidefinite programming, harmonic analysis and coding theory
|
cs.IT math.IT
|
These lecture notes where presented as a course of the CIMPA summer school in
Manila, July 20-30, 2009, Semidefinite programming in algebraic combinatorics.
This version is an update June 2010.
|
0909.4807
|
Consensus in Correlated Random Topologies: Weights for Finite Time
Horizon
|
cs.IT math.IT
|
We consider the weight design problem for the consensus algorithm under a
finite time horizon. We assume that the underlying network is random where the
links fail at each iteration with certain probability and the link failures can
be spatially correlated. We formulate a family of weight design criteria
(objective functions) that minimize n, n = 1,...,N (out of N possible) largest
(slowest) eigenvalues of the matrix that describes the mean squared consensus
error dynamics. We show that the objective functions are convex; hence,
globally optimal weights (with respect to the design criteria) can be
efficiently obtained. Numerical examples on large scale, sparse random networks
with spatially correlated link failures show that: 1) weights obtained
according to our criteria lead to significantly faster convergence than the
choices available in the literature; 2) different design criteria that
corresponds to different n, exhibits very interesting tradeoffs: faster
transient performance leads to slower long time run performance and vice versa.
Thus, n is a valuable degree of freedom and can be appropriately selected for
the given time horizon.
|
0909.4808
|
Combinatiorial Algorithms for Wireless Information Flow
|
cs.DS cs.IT math.IT
|
A long-standing open question in information theory is to characterize the
unicast capacity of a wireless relay network. The difficulty arises due to the
complex signal interactions induced in the network, since the wireless channel
inherently broadcasts the signals and there is interference among
transmissions. Recently, Avestimehr, Diggavi and Tse proposed a linear
deterministic model that takes into account the shared nature of wireless
channels, focusing on the signal interactions rather than the background noise.
They generalized the min-cut max-flow theorem for graphs to networks of
deterministic channels and proved that the capacity can be achieved using
information theoretical tools. They showed that the value of the minimum cut is
in this case the minimum rank of all the adjacency matrices describing
source-destination cuts.
In this paper, we develop a polynomial time algorithm that discovers the
relay encoding strategy to achieve the min-cut value in linear deterministic
(wireless) networks, for the case of a unicast connection. Our algorithm
crucially uses a notion of linear independence between channels to calculate
the capacity in polynomial time. Moreover, we can achieve the capacity by using
very simple one-symbol processing at the intermediate nodes, thereby
constructively yielding finite length strategies that achieve the unicast
capacity of the linear deterministic (wireless) relay network.
|
0909.4828
|
Optimal Feedback Communication via Posterior Matching
|
cs.IT math.IT
|
In this paper we introduce a fundamental principle for optimal communication
over general memoryless channels in the presence of noiseless feedback, termed
posterior matching. Using this principle, we devise a (simple, sequential)
generic feedback transmission scheme suitable for a large class of memoryless
channels and input distributions, achieving any rate below the corresponding
mutual information. This provides a unified framework for optimal feedback
communication in which the Horstein scheme (BSC) and the Schalkwijk-Kailath
scheme (AWGN channel) are special cases. Thus, as a corollary, we prove that
the Horstein scheme indeed attains the BSC capacity, settling a longstanding
conjecture. We further provide closed form expressions for the error
probability of the scheme over a range of rates, and derive the achievable
rates in a mismatch setting where the scheme is designed according to the wrong
channel model. Several illustrative examples of the posterior matching scheme
for specific channels are given, and the corresponding error probability
expressions are evaluated. The proof techniques employed utilize novel
relations between information rates and contraction properties of iterated
function systems.
|
0909.4830
|
Super-wavelets versus poly-Bergman spaces
|
math.FA cs.IT math.IT
|
Motivated by potential applications in multiplexing and by recent results on
Gabor analysis with Hermite windows due to Gr\"{o}chenig and Lyubarskii, we
investigate vector-valued wavelet transforms and vector-valued wavelet frames,
which constitute special cases of super-wavelets, with a particular attention
to the case when the analyzing wavelet vector is related to Fourier transforms
of Laguerre functions. We construct an isometric isomorphism between
$L^{2}(\mathbb{R}^{+},\mathbf{C}^{n})$ and poly-Bergman spaces, with a view to
relate the sampling sequences in the poly-Bergman spaces to the wavelet frames
and super-frames with the windows $\Phi_{n}$. One of the applications of the
theory is a proof that $b\ln a<2\pi (n+1)$ is a necessary condition for the
(scalar) wavelet frame associated to the $\Phi_{n}$ to exist. This seems to be
the first known result of this type outside the setting of analytic functions
(the case $n=0$, which has been completely studied by Seip in 1993).
|
0909.4876
|
A Program in Dialectical Rough Set Theory
|
math.LO cs.IT math.IT
|
A dialectical rough set theory focussed on the relation between roughly
equivalent objects and classical objects was introduced in \cite{AM699} by the
present author. The focus of our investigation is on elucidating the minimal
conditions on the nature of granularity, underlying semantic domain and nature
of the general rough set theories (RST) involved for possible extension of the
semantics to more general RST on a paradigm. On this basis we also formulate a
program in dialectical rough set theory. The dialectical approach provides
better semantics in many difficult cases and helps in formalising a wide
variety of concepts and notions that remain untamed at meta levels in the usual
approaches. This is a brief version of a more detailed forthcoming paper by the
present author.
|
0909.4889
|
Hybrid Intrusion Detection and Prediction multiAgent System HIDPAS
|
cs.CR cs.AI cs.DS
|
This paper proposes an intrusion detection and prediction system based on
uncertain and imprecise inference networks and its implementation. Giving a
historic of sessions, it is about proposing a method of supervised learning
doubled of a classifier permitting to extract the necessary knowledge in order
to identify the presence or not of an intrusion in a session and in the
positive case to recognize its type and to predict the possible intrusions that
will follow it. The proposed system takes into account the uncertainty and
imprecision that can affect the statistical data of the historic. The
systematic utilization of an unique probability distribution to represent this
type of knowledge supposes a too rich subjective information and risk to be in
part arbitrary. One of the first objectives of this work was therefore to
permit the consistency between the manner of which we represent information and
information which we really dispose.
|
0909.4938
|
Empirical analysis of web-based user-object bipartite networks
|
physics.data-an cs.IR physics.soc-ph
|
Understanding the structure and evolution of web-based user-object networks
is a significant task since they play a crucial role in e-commerce nowadays.
This Letter reports the empirical analysis on two large-scale web sites,
audioscrobbler.com and del.icio.us, where users are connected with music groups
and bookmarks, respectively. The degree distributions and degree-degree
correlations for both users and objects are reported. We propose a new index,
named collaborative clustering coefficient, to quantify the clustering behavior
based on the collaborative selection. Accordingly, the clustering properties
and clustering-degree correlations are investigated. We report some novel
phenomena well characterizing the selection mechanism of web users and outline
the relevance of these phenomena to the information recommendation problem.
|
0909.4983
|
Event-Driven Optimal Feedback Control for Multi-Antenna Beamforming
|
cs.IT math.IT
|
Transmit beamforming is a simple multi-antenna technique for increasing
throughput and the transmission range of a wireless communication system. The
required feedback of channel state information (CSI) can potentially result in
excessive overhead especially for high mobility or many antennas. This work
concerns efficient feedback for transmit beamforming and establishes a new
approach of controlling feedback for maximizing net throughput, defined as
throughput minus average feedback cost. The feedback controller using a
stationary policy turns CSI feedback on/off according to the system state that
comprises the channel state and transmit beamformer. Assuming channel isotropy
and Markovity, the controller's state reduces to two scalars. This allows the
optimal control policy to be efficiently computed using dynamic programming.
Consider the perfect feedback channel free of error, where each feedback
instant pays a fixed price. The corresponding optimal feedback control policy
is proved to be of the threshold type. This result holds regardless of whether
the controller's state space is discretized or continuous. Under the
threshold-type policy, feedback is performed whenever a state variable
indicating the accuracy of transmit CSI is below a threshold, which varies with
channel power. The practical finite-rate feedback channel is also considered.
The optimal policy for quantized feedback is proved to be also of the threshold
type. The effect of CSI quantization is shown to be equivalent to an increment
on the feedback price. Moreover, the increment is upper bounded by the expected
logarithm of one minus the quantization error. Finally, simulation shows that
feedback control increases net throughput of the conventional periodic feedback
by up to 0.5 bit/s/Hz without requiring additional bandwidth or antennas.
|
0909.4995
|
Geometrical Interpretation of Shannon's Entropy Based on the Born Rule
|
cs.IT cs.NE math.IT math.PR physics.data-an
|
In this paper we will analyze discrete probability distributions in which
probabilities of particular outcomes of some experiment (microstates) can be
represented by the ratio of natural numbers (in other words, probabilities are
represented by digital numbers of finite representation length). We will
introduce several results that are based on recently proposed JoyStick
Probability Selector, which represents a geometrical interpretation of the
probability based on the Born rule. The terms of generic space and generic
dimension of the discrete distribution, as well as, effective dimension are
going to be introduced. It will be shown how this simple geometric
representation can lead to an optimal code length coding of the sequence of
signals. Then, we will give a new, geometrical, interpretation of the Shannon
entropy of the discrete distribution. We will suggest that the Shannon entropy
represents the logarithm of the effective dimension of the distribution.
Proposed geometrical interpretation of the Shannon entropy can be used to prove
some information inequalities in an elementary way.
|
0909.5000
|
Eignets for function approximation on manifolds
|
cs.LG cs.NA cs.NE
|
Let $\XX$ be a compact, smooth, connected, Riemannian manifold without
boundary, $G:\XX\times\XX\to \RR$ be a kernel. Analogous to a radial basis
function network, an eignet is an expression of the form $\sum_{j=1}^M
a_jG(\circ,y_j)$, where $a_j\in\RR$, $y_j\in\XX$, $1\le j\le M$. We describe a
deterministic, universal algorithm for constructing an eignet for approximating
functions in $L^p(\mu;\XX)$ for a general class of measures $\mu$ and kernels
$G$. Our algorithm yields linear operators. Using the minimal separation
amongst the centers $y_j$ as the cost of approximation, we give modulus of
smoothness estimates for the degree of approximation by our eignets, and show
by means of a converse theorem that these are the best possible for every
\emph{individual function}. We also give estimates on the coefficients $a_j$ in
terms of the norm of the eignet. Finally, we demonstrate that if any sequence
of eignets satisfies the optimal estimates for the degree of approximation of a
smooth function, measured in terms of the minimal separation, then the
derivatives of the eignets also approximate the corresponding derivatives of
the target function in an optimal manner.
|
0909.5006
|
On the Degrees of Freedom of the Compound MIMO Broadcast Channels with
Finite States
|
cs.IT math.IT
|
Multiple-antenna broadcast channels with $M$ transmit antennas and $K$
single-antenna receivers is considered, where the channel of receiver $r$ takes
one of the $J_r$ finite values. It is assumed that the channel states of each
receiver are randomly selected from $\mathds{R}^{M\times 1}$ (or from
$\mathds{C}^{M\times 1}$). It is shown that no matter what $J_r$ is, the
degrees of freedom (DoF) of $\frac{MK}{M+K-1}$ is achievable. The achievable
scheme relies on the idea of interference alignment at receivers, without
exploiting the possibility of cooperation among transmit antennas. It is proven
that if $J_r \geq M$, $r=1,...,K$, this scheme achieves the optimal DoF. This
results implies that when the uncertainty of the base station about the channel
realization is considerable, the system loses the gain of cooperation. However,
it still benefits from the gain of interference alignment. In fact, in this
case, the compound broadcast channel is treated as a compound X channel.
Moreover, it is shown that when the base station knows the channel states of
some of the receivers, a combination of transmit cooperation and interference
alignment would achieve the optimal DoF.
Like time-invariant $K$-user interference channels, the naive vector-space
approaches of interference management seem insufficient to achieve the optimal
DoF of this channel. In this paper, we use the Number-Theory approach of
alignment, recently developed by Motahari et al.[1]. We extend the approach of
[1] to complex channels as well, therefore all the results that we present are
valid for both real and complex channels.
|
0909.5007
|
Achieving Capacity of Bi-Directional Tandem Collision Network by Joint
Medium-Access Control and Channel-Network Coding
|
cs.IT math.IT
|
In ALOHA-type packetized network, the transmission times of packets follow a
stochastic process. In this paper, we advocate a deterministic approach for
channel multiple-access. Each user is statically assigned a periodic protocol
signal, which takes value either zero or one, and transmit packets whenever the
value of the protocol signal is equal to one. On top of this multiple-access
protocol, efficient channel coding and network coding schemes are devised. We
illustrate the idea by constructing a transmission scheme for the tandem
collision network, for both slot-synchronous and slot-asynchronous systems.
This cross-layer approach is able to achieve the capacity region when the
network is bi-directional.
|
0909.5012
|
IRPF90: a programming environment for high performance computing
|
cs.SE cs.CE
|
IRPF90 is a Fortran programming environment which helps the development of
large Fortran codes. In Fortran programs, the programmer has to focus on the
order of the instructions: before using a variable, the programmer has to be
sure that it has already been computed in all possible situations. For large
codes, it is common source of error. In IRPF90 most of the order of
instructions is handled by the pre-processor, and an automatic mechanism
guarantees that every entity is built before being used. This mechanism relies
on the {needs/needed by} relations between the entities, which are built
automatically. Codes written with IRPF90 execute often faster than Fortran
programs, are faster to write and easier to maintain.
|
0909.5097
|
On the Scope of the Universal-Algebraic Approach to Constraint
Satisfaction
|
cs.LO cs.AI cs.CC
|
The universal-algebraic approach has proved a powerful tool in the study of
the complexity of CSPs. This approach has previously been applied to the study
of CSPs with finite or (infinite) omega-categorical templates, and relies on
two facts. The first is that in finite or omega-categorical structures A, a
relation is primitive positive definable if and only if it is preserved by the
polymorphisms of A. The second is that every finite or omega-categorical
structure is homomorphically equivalent to a core structure. In this paper, we
present generalizations of these facts to infinite structures that are not
necessarily omega-categorical. (This abstract has been severely curtailed by
the space constraints of arXiv -- please read the full abstract in the
article.) Finally, we present applications of our general results to the
description and analysis of the complexity of CSPs. In particular, we give
general hardness criteria based on the absence of polymorphisms that depend on
more than one argument, and we present a polymorphism-based description of
those CSPs that are first-order definable (and therefore can be solved in
polynomial time).
|
0909.5099
|
Breaking Generator Symmetry
|
cs.AI cs.CC
|
Dealing with large numbers of symmetries is often problematic. One solution
is to focus on just symmetries that generate the symmetry group. Whilst there
are special cases where breaking just the symmetries in a generating set is
complete, there are also cases where no irredundant generating set eliminates
all symmetry. However, focusing on just generators improves tractability. We
prove that it is polynomial in the size of the generating set to eliminate all
symmetric solutions, but NP-hard to prune all symmetric values. Our proof
considers row and column symmetry, a common type of symmetry in matrix models
where breaking just generator symmetries is very effective. We show that
propagating a conjunction of lexicographical ordering constraints on the rows
and columns of a matrix of decision variables is NP-hard.
|
0909.5119
|
Random Access Transport Capacity
|
cs.IT math.IT
|
We develop a new metric for quantifying end-to-end throughput in multihop
wireless networks, which we term random access transport capacity, since the
interference model presumes uncoordinated transmissions. The metric quantifies
the average maximum rate of successful end-to-end transmissions, multiplied by
the communication distance, and normalized by the network area. We show that a
simple upper bound on this quantity is computable in closed-form in terms of
key network parameters when the number of retransmissions is not restricted and
the hops are assumed to be equally spaced on a line between the source and
destination. We also derive the optimum number of hops and optimal per hop
success probability and show that our result follows the well-known square root
scaling law while providing exact expressions for the preconstants as well.
Numerical results demonstrate that the upper bound is accurate for the purpose
of determining the optimal hop count and success (or outage) probability.
|
0909.5120
|
Feedback-Based Collaborative Secrecy Encoding over Binary Symmetric
Channels
|
cs.IT cs.CR math.IT
|
In this paper we propose a feedback scheme for transmitting secret messages
between two legitimate parties, over an eavesdropped communication link.
Relative to Wyner's traditional encoding scheme \cite{wyner1}, our
feedback-based encoding often yields larger rate-equivocation regions and
achievable secrecy rates. More importantly, by exploiting the channel
randomness inherent in the feedback channels, our scheme achieves a strictly
positive secrecy rate even when the eavesdropper's channel is less noisy than
the legitimate receiver's channel. All channels are modeled as binary and
symmetric (BSC). We demonstrate the versatility of our feedback-based encoding
method by using it in three different configurations: the stand-alone
configuration, the mixed configuration (when it combines with Wyner's scheme
\cite{wyner1}), and the reversed configuration. Depending on the channel
conditions, significant improvements over Wyner's secrecy capacity can be
observed in all configurations.
|
0909.5166
|
An Algorithm for Mining Multidimensional Fuzzy Association Rules
|
cs.IR cs.DB
|
Multidimensional association rule mining searches for interesting
relationship among the values from different dimensions or attributes in a
relational database. In this method the correlation is among set of dimensions
i.e., the items forming a rule come from different dimensions. Therefore each
dimension should be partitioned at the fuzzy set level. This paper proposes a
new algorithm for generating multidimensional association rules by utilizing
fuzzy sets. A database consisting of fuzzy transactions, the Apriory property
is employed to prune the useless candidates, itemsets.
|
0909.5175
|
Bounding the Sensitivity of Polynomial Threshold Functions
|
cs.CC cs.LG
|
We give the first non-trivial upper bounds on the average sensitivity and
noise sensitivity of polynomial threshold functions. More specifically, for a
Boolean function f on n variables equal to the sign of a real, multivariate
polynomial of total degree d we prove
1) The average sensitivity of f is at most O(n^{1-1/(4d+6)}) (we also give a
combinatorial proof of the bound O(n^{1-1/2^d}).
2) The noise sensitivity of f with noise rate \delta is at most
O(\delta^{1/(4d+6)}).
Previously, only bounds for the linear case were known. Along the way we show
new structural theorems about random restrictions of polynomial threshold
functions obtained via hypercontractivity. These structural results may be of
independent interest as they provide a generic template for transforming
problems related to polynomial threshold functions defined on the Boolean
hypercube to polynomial threshold functions defined in Gaussian space.
|
0909.5179
|
Expected RIP: Conditioning of The Modulated Wideband Converter
|
cs.IT math.IT
|
The sensing matrix of a compressive system impacts the stability of the
associated sparse recovery problem. In this paper, we study the sensing matrix
of the modulated wideband converter, a recently proposed system for sub-Nyquist
sampling of analog sparse signals. Attempting to quantify the conditioning of
the converter sensing matrix with existing approaches leads to unreasonable
rate requirements, due to the relatively small size of this matrix. We propose
a new conditioning criterion, named the expected restricted isometry property,
and derive theoretical guarantees for the converter to satisfy this property.
We then show that applying these conditions to popular binary sequences, such
as maximal codes or Gold codes, leads to practical rate requirements.
|
0909.5216
|
Learning Gaussian Tree Models: Analysis of Error Exponents and Extremal
Structures
|
stat.ML cs.IT math.IT math.ST stat.TH
|
The problem of learning tree-structured Gaussian graphical models from
independent and identically distributed (i.i.d.) samples is considered. The
influence of the tree structure and the parameters of the Gaussian distribution
on the learning rate as the number of samples increases is discussed.
Specifically, the error exponent corresponding to the event that the estimated
tree structure differs from the actual unknown tree structure of the
distribution is analyzed. Finding the error exponent reduces to a least-squares
problem in the very noisy learning regime. In this regime, it is shown that the
extremal tree structure that minimizes the error exponent is the star for any
fixed set of correlation coefficients on the edges of the tree. If the
magnitudes of all the correlation coefficients are less than 0.63, it is also
shown that the tree structure that maximizes the error exponent is the Markov
chain. In other words, the star and the chain graphs represent the hardest and
the easiest structures to learn in the class of tree-structured Gaussian
graphical models. This result can also be intuitively explained by correlation
decay: pairs of nodes which are far apart, in terms of graph distance, are
unlikely to be mistaken as edges by the maximum-likelihood estimator in the
asymptotic regime.
|
0909.5268
|
A Simple Necessary and Sufficient Condition for the Double Unicast
Problem
|
cs.IT math.IT
|
We consider a directed acyclic network where there are two source-terminal
pairs and the terminals need to receive the symbols generated at the respective
sources. Each source independently generates an i.i.d. random process over the
same alphabet. Each edge in the network is error-free, delay-free, and can
carry one symbol from the alphabet per use. We give a simple necessary and
sufficient condition for being able to simultaneously satisfy the unicast
requirements of the two source-terminal pairs at rate-pair $(1,1)$ using vector
network coding. The condition is also sufficient for doing this using only
"XOR" network coding and is much simpler compared to the necessary and
sufficient conditions known from previous work. Our condition also yields a
simple characterization of the capacity region of a double-unicast network
which does not support the rate-pair $(1,1)$.
|
0909.5310
|
Cognitive Power Control Under Correlated Fading and Primary-Link CSI
|
cs.IT math.IT
|
We consider the cognitive power control problem of maximizing the secondary
throughput under an outage probability constraint on a constant-power
constant-rate primary link. We assume a temporally correlated primary channel
with two types of feedback: perfect delayed channel state information (CSI) and
one-bit automatic repeat request (ARQ). We use channel correlation to enhance
the primary and secondary throughput via exploiting the CSI feedback to predict
the future primary channel gain. We provide a numerical solution for the power
control optimization problem under delayed CSI. In order to make the solution
tractable under ARQ-CSI, we re-formulate the cognitive power control problem as
the maximization of the instantaneous weighted sum of primary and secondary
throughput. We propose a greedy ARQ-CSI algorithm that is shown to achieve an
average throughput comparable to that attained under the delayed-CSI algorithm,
which we solve optimally.
|
0909.5424
|
The Degrees of Freedom Regions of MIMO Broadcast, Interference, and
Cognitive Radio Channels with No CSIT
|
cs.IT math.IT
|
The degrees of freedom (DoF) regions are characterized for the multiple-input
multiple-output (MIMO) broadcast channel (BC), interference channels (IC)
(including X and multi-hop interference channels) and the cognitive radio
channel (CRC), when there is perfect and no channel state information at the
receivers and the transmitter(s) (CSIR and CSIT), respectively. For the K-user
MIMO BC, the exact characterization of the DoF region is obtained, which shows
that a simple time-division-based transmission scheme is DoF-region optimal.
Using the techniques developed for the MIMO BC, the corresponding problems for
the two-user MIMO IC and the CRC are addressed. For both of these channels,
inner and outer bounds to the DoF region are obtained and are seen to coincide
for a vast majority of the relative numbers of antennas at the four terminals,
thereby characterizing DoF regions for all but a few cases. Finally, the DoF
regions of the $K$-user MIMO IC, the CRC, and X networks are derived for
certain classes of these networks, including the one where all transmitters
have an equal number of antennas and so do all receivers. The results of this
paper are derived for distributions of fading channel matrices and additive
noises that are more general than those considered in other simultaneous
related works. The DoF regions with and without CSIT are compared and
conditions on the relative numbers of antennas at the terminals under which a
lack of CSIT does, or does not, result in the loss of DoF are identified,
thereby providing, on the one hand, simple and robust communication schemes
that don't require CSIT but have the same DoF performance as their previously
found CSIT counterparts, and on the other hand, identifying situations where
CSI feedback to transmitters would provide gains that are significant enough
that even the DoF performance could be improved.
|
0909.5450
|
Robust Distributed Estimation over Multiple Access Channels with
Constant Modulus Signaling
|
cs.IT math.IT
|
A distributed estimation scheme where the sensors transmit with constant
modulus signals over a multiple access channel is considered. The proposed
estimator is shown to be strongly consistent for any sensing noise distribution
in the i.i.d. case both for a per-sensor power constraint, and a total power
constraint. When the distributions of the sensing noise are not identical, a
bound on the variances is shown to establish strong consistency. The estimator
is shown to be asymptotically normal with a variance (AsV) that depends on the
characteristic function of the sensing noise. Optimization of the AsV is
considered with respect to a transmission phase parameter for a variety of
noise distributions exhibiting differing levels of impulsive behavior. The
robustness of the estimator to impulsive sensing noise distributions such as
those with positive excess kurtosis, or those that do not have finite moments
is shown. The proposed estimator is favorably compared with the amplify and
forward scheme under an impulsive noise scenario. The effect of fading is shown
to not affect the consistency of the estimator, but to scale the asymptotic
variance by a constant fading penalty depending on the fading statistics.
Simulations corroborate our analytical results.
|
0909.5457
|
Guaranteed Rank Minimization via Singular Value Projection
|
cs.LG cs.IT math.IT
|
Minimizing the rank of a matrix subject to affine constraints is a
fundamental problem with many important applications in machine learning and
statistics. In this paper we propose a simple and fast algorithm SVP (Singular
Value Projection) for rank minimization with affine constraints (ARMP) and show
that SVP recovers the minimum rank solution for affine constraints that satisfy
the "restricted isometry property" and show robustness of our method to noise.
Our results improve upon a recent breakthrough by Recht, Fazel and Parillo
(RFP07) and Lee and Bresler (LB09) in three significant ways:
1) our method (SVP) is significantly simpler to analyze and easier to
implement,
2) we give recovery guarantees under strictly weaker isometry assumptions
3) we give geometric convergence guarantees for SVP even in presense of noise
and, as demonstrated empirically, SVP is significantly faster on real-world and
synthetic problems.
In addition, we address the practically important problem of low-rank matrix
completion (MCP), which can be seen as a special case of ARMP. We empirically
demonstrate that our algorithm recovers low-rank incoherent matrices from an
almost optimal number of uniformly sampled entries. We make partial progress
towards proving exact recovery and provide some intuition for the strong
performance of SVP applied to matrix completion by showing a more restricted
isometry property. Our algorithm outperforms existing methods, such as those of
\cite{RFP07,CR08,CT09,CCS08,KOM09,LB09}, for ARMP and the matrix-completion
problem by an order of magnitude and is also significantly more robust to
noise.
|
0909.5458
|
Information tracking approach to segmentation of ultrasound imagery of
prostate
|
cs.CV
|
The size and geometry of the prostate are known to be pivotal quantities used
by clinicians to assess the condition of the gland during prostate cancer
screening. As an alternative to palpation, an increasing number of methods for
estimation of the above-mentioned quantities are based on using imagery data of
prostate. The necessity to process large volumes of such data creates a need
for automatic segmentation tools which would allow the estimation to be carried
out with maximum accuracy and efficiency. In particular, the use of transrectal
ultrasound (TRUS) imaging in prostate cancer screening seems to be becoming a
standard clinical practice due to the high benefit-to-cost ratio of this
imaging modality. Unfortunately, the segmentation of TRUS images is still
hampered by relatively low contrast and reduced SNR of the images, thereby
requiring the segmentation algorithms to incorporate prior knowledge about the
geometry of the gland. In this paper, a novel approach to the problem of
segmenting the TRUS images is described. The proposed approach is based on the
concept of distribution tracking, which provides a unified framework for
modeling and fusing image-related and morphological features of the prostate.
Moreover, the same framework allows the segmentation to be regularized via
using a new type of "weak" shape priors, which minimally bias the estimation
procedure, while rendering the latter stable and robust.
|
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