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1205.4471
|
Sparse Signal Recovery in the Presence of Intra-Vector and Inter-Vector
Correlation
|
cs.IT cs.LG math.IT stat.ME stat.ML
|
This work discusses the problem of sparse signal recovery when there is
correlation among the values of non-zero entries. We examine intra-vector
correlation in the context of the block sparse model and inter-vector
correlation in the context of the multiple measurement vector model, as well as
their combination. Algorithms based on the sparse Bayesian learning are
presented and the benefits of incorporating correlation at the algorithm level
are discussed. The impact of correlation on the limits of support recovery is
also discussed highlighting the different impact intra-vector and inter-vector
correlations have on such limits.
|
1205.4476
|
Soft Rule Ensembles for Statistical Learning
|
stat.ML cs.LG stat.AP
|
In this article supervised learning problems are solved using soft rule
ensembles. We first review the importance sampling learning ensembles (ISLE)
approach that is useful for generating hard rules. The soft rules are then
obtained with logistic regression from the corresponding hard rules. In order
to deal with the perfect separation problem related to the logistic regression,
Firth's bias corrected likelihood is used. Various examples and simulation
results show that soft rule ensembles can improve predictive performance over
hard rule ensembles.
|
1205.4477
|
Streaming Algorithms for Pattern Discovery over Dynamically Changing
Event Sequences
|
cs.LG cs.DB
|
Discovering frequent episodes over event sequences is an important data
mining task. In many applications, events constituting the data sequence arrive
as a stream, at furious rates, and recent trends (or frequent episodes) can
change and drift due to the dynamical nature of the underlying event generation
process. The ability to detect and track such the changing sets of frequent
episodes can be valuable in many application scenarios. Current methods for
frequent episode discovery are typically multipass algorithms, making them
unsuitable in the streaming context. In this paper, we propose a new streaming
algorithm for discovering frequent episodes over a window of recent events in
the stream. Our algorithm processes events as they arrive, one batch at a time,
while discovering the top frequent episodes over a window consisting of several
batches in the immediate past. We derive approximation guarantees for our
algorithm under the condition that frequent episodes are approximately
well-separated from infrequent ones in every batch of the window. We present
extensive experimental evaluations of our algorithm on both real and synthetic
data. We also present comparisons with baselines and adaptations of streaming
algorithms from itemset mining literature.
|
1205.4481
|
Stochastic Smoothing for Nonsmooth Minimizations: Accelerating SGD by
Exploiting Structure
|
cs.LG stat.CO stat.ML
|
In this work we consider the stochastic minimization of nonsmooth convex loss
functions, a central problem in machine learning. We propose a novel algorithm
called Accelerated Nonsmooth Stochastic Gradient Descent (ANSGD), which
exploits the structure of common nonsmooth loss functions to achieve optimal
convergence rates for a class of problems including SVMs. It is the first
stochastic algorithm that can achieve the optimal O(1/t) rate for minimizing
nonsmooth loss functions (with strong convexity). The fast rates are confirmed
by empirical comparisons, in which ANSGD significantly outperforms previous
subgradient descent algorithms including SGD.
|
1205.4546
|
Latent Multi-group Membership Graph Model
|
cs.SI physics.soc-ph stat.ML
|
We develop the Latent Multi-group Membership Graph (LMMG) model, a model of
networks with rich node feature structure. In the LMMG model, each node belongs
to multiple groups and each latent group models the occurrence of links as well
as the node feature structure. The LMMG can be used to summarize the network
structure, to predict links between the nodes, and to predict missing features
of a node. We derive efficient inference and learning algorithms and evaluate
the predictive performance of the LMMG on several social and document network
datasets.
|
1205.4551
|
Sparse Signal Separation in Redundant Dictionaries
|
cs.IT math.IT
|
We formulate a unified framework for the separation of signals that are
sparse in "morphologically" different redundant dictionaries. This formulation
incorporates the so-called "analysis" and "synthesis" approaches as special
cases and contains novel hybrid setups. We find corresponding coherence-based
recovery guarantees for an l1-norm based separation algorithm. Our results
recover those reported in Studer and Baraniuk, ACHA, submitted, for the
synthesis setting, provide new recovery guarantees for the analysis setting,
and form a basis for comparing performance in the analysis and synthesis
settings. As an aside our findings complement the D-RIP recovery results
reported in Cand\`es et al., ACHA, 2011, for the "analysis" signal recovery
problem: minimize_x ||{\Psi}x||_1 subject to ||y - Ax||_2 \leq {\epsilon}, by
delivering corresponding coherence-based recovery results.
|
1205.4583
|
Sparse Signal Recovery in Hilbert Spaces
|
cs.IT math.IT
|
This paper reports an effort to consolidate numerous coherence-based sparse
signal recovery results available in the literature. We present a single theory
that applies to general Hilbert spaces with the sparsity of a signal defined as
the number of (possibly infinite-dimensional) subspaces participating in the
signal's representation. Our general results recover uncertainty relations and
coherence-based recovery thresholds for sparse signals, block-sparse signals,
multi-band signals, signals in shift-invariant spaces, and signals in finite
unions of (possibly infinite-dimensional) subspaces. Moreover, we improve upon
and generalize several of the existing results and, in many cases, we find
shortened and simplified proofs.
|
1205.4639
|
Observer Design for Takagi-Sugeno Descriptor System with Lipschitz
Constraints
|
cs.SY
|
This paper investigates the design problem of observers for nonlinear
descriptor systems described by Takagi-Sugeno (TS) system; Depending on the
available knowledge on the premise variables two cases are considered. First a
TS descriptor system with measurables premises variables are proposed. Second,
an observer design which satisfying the Lipschitz condition is proposed when
the premises variables are unmeasurables. The convergence of the state
estimation error is studied using the Lyapunov theory and the stability
conditions are given in terms of Linear Matrix Inequalities (LMIs). Examples
are included to illustrate those methods.
|
1205.4641
|
Parity Check Matrix Recognition from Noisy Codewords
|
cs.IT math.IT
|
We study recovering parity check relations for an unknown code from
intercepted bitstream received from Binary Symmetric Channel in this paper. An
iterative column elimination algorithm is introduced which attempts to
eliminate parity bits in codewords of noisy data. This algorithm is very
practical due to low complexity and use of XOR operator. Since, the
computational complexity is low, searching for the length of code and
synchronization is possible. Furthermore, the Hamming weight of the parity
check words are only used in threshold computation and unlike other algorithms,
they have negligible effect in the proposed algorithm. Eventually, experimental
results are presented and estimations for the maximum noise level allowed for
recovering the words of the parity check matrix are investigated.
|
1205.4655
|
The View-Update Problem for Indefinite Databases
|
cs.DB cs.AI
|
This paper introduces and studies a declarative framework for updating views
over indefinite databases. An indefinite database is a database with null
values that are represented, following the standard database approach, by a
single null constant. The paper formalizes views over such databases as
indefinite deductive databases, and defines for them several classes of
database repairs that realize view-update requests. Most notable is the class
of constrained repairs. Constrained repairs change the database "minimally" and
avoid making arbitrary commitments. They narrow down the space of alternative
ways to fulfill the view-update request to those that are grounded, in a
certain strong sense, in the database, the view and the view-update request.
|
1205.4656
|
Conditional mean embeddings as regressors - supplementary
|
cs.LG stat.ML
|
We demonstrate an equivalence between reproducing kernel Hilbert space (RKHS)
embeddings of conditional distributions and vector-valued regressors. This
connection introduces a natural regularized loss function which the RKHS
embeddings minimise, providing an intuitive understanding of the embeddings and
a justification for their use. Furthermore, the equivalence allows the
application of vector-valued regression methods and results to the problem of
learning conditional distributions. Using this link we derive a sparse version
of the embedding by considering alternative formulations. Further, by applying
convergence results for vector-valued regression to the embedding problem we
derive minimax convergence rates which are O(\log(n)/n) -- compared to current
state of the art rates of O(n^{-1/4}) -- and are valid under milder and more
intuitive assumptions. These minimax upper rates coincide with lower rates up
to a logarithmic factor, showing that the embedding method achieves nearly
optimal rates. We study our sparse embedding algorithm in a reinforcement
learning task where the algorithm shows significant improvement in sparsity
over an incomplete Cholesky decomposition.
|
1205.4673
|
Minimum Complexity Pursuit: Stability Analysis
|
cs.IT math.IT
|
A host of problems involve the recovery of structured signals from a
dimensionality reduced representation such as a random projection; examples
include sparse signals (compressive sensing) and low-rank matrices (matrix
completion). Given the wide range of different recovery algorithms developed to
date, it is natural to ask whether there exist "universal" algorithms for
recovering "structured" signals from their linear projections. We recently
answered this question in the affirmative in the noise-free setting. In this
paper, we extend our results to the case of noisy measurements.
|
1205.4674
|
Capacity and coding for the Ising Channel with Feedback
|
cs.IT math.IT
|
The Ising channel, which was introduced in 1990, is a channel with memory
that models Inter-Symbol interference. In this paper we consider the Ising
channel with feedback and find the capacity of the channel together with a
capacity-achieving coding scheme. To calculate the channel capacity, an
equivalent dynamic programming (DP) problem is formulated and solved. Using the
DP solution, we establish that the feedback capacity is the expression
$C=(\frac{2H_b(a)}{3+a})\approx 0.575522$ where $a$ is a particular root of a
fourth-degree polynomial and $H_b(x)$ denotes the binary entropy function.
Simultaneously, $a=\arg \max_{0\leq x \leq 1} (\frac{2H_b(x)}{3+x})$. Finally,
a simple, error-free, capacity-achieving coding scheme is provided together
with outlining a strong connection between the DP results and the coding
scheme.
|
1205.4683
|
How women organize social networks different from men
|
physics.soc-ph cs.SI
|
Superpositions of social networks, such as communication, friendship, or
trade networks, are called multiplex networks, forming the structural backbone
of human societies. Novel datasets now allow quantification and exploration of
multiplex networks. Here we study gender-specific differences of a multiplex
network from a complete behavioral dataset of an online-game society of about
300,000 players. On the individual level females perform better economically
and are less risk-taking than males. Males reciprocate friendship requests from
females faster than vice versa and hesitate to reciprocate hostile actions of
females. On the network level females have more communication partners, who are
less connected than partners of males. We find a strong homophily effect for
females and higher clustering coefficients of females in trade and attack
networks. Cooperative links between males are under-represented, reflecting
competition for resources among males. These results confirm quantitatively
that females and males manage their social networks in substantially different
ways.
|
1205.4698
|
The Role of Weight Shrinking in Large Margin Perceptron Learning
|
cs.LG
|
We introduce into the classical perceptron algorithm with margin a mechanism
that shrinks the current weight vector as a first step of the update. If the
shrinking factor is constant the resulting algorithm may be regarded as a
margin-error-driven version of NORMA with constant learning rate. In this case
we show that the allowed strength of shrinking depends on the value of the
maximum margin. We also consider variable shrinking factors for which there is
no such dependence. In both cases we obtain new generalizations of the
perceptron with margin able to provably attain in a finite number of steps any
desirable approximation of the maximal margin hyperplane. The new approximate
maximum margin classifiers appear experimentally to be very competitive in
2-norm soft margin tasks involving linear kernels.
|
1205.4776
|
Visual and semantic interpretability of projections of high dimensional
data for classification tasks
|
cs.HC cs.LG
|
A number of visual quality measures have been introduced in visual analytics
literature in order to automatically select the best views of high dimensional
data from a large number of candidate data projections. These methods generally
concentrate on the interpretability of the visualization and pay little
attention to the interpretability of the projection axes. In this paper, we
argue that interpretability of the visualizations and the feature
transformation functions are both crucial for visual exploration of high
dimensional labeled data. We present a two-part user study to examine these two
related but orthogonal aspects of interpretability. We first study how humans
judge the quality of 2D scatterplots of various datasets with varying number of
classes and provide comparisons with ten automated measures, including a number
of visual quality measures and related measures from various machine learning
fields. We then investigate how the user perception on interpretability of
mathematical expressions relate to various automated measures of complexity
that can be used to characterize data projection functions. We conclude with a
discussion of how automated measures of visual and semantic interpretability of
data projections can be used together for exploratory analysis in
classification tasks.
|
1205.4781
|
An Achievable Rate Region for Three-Pair Interference Channels with
Noise
|
cs.IT math.IT
|
An achievable rate region for certain noisy three-user-pair interference
channels is proposed. The channel class under consideration generalizes the
three-pair deterministic interference channel (3-DIC) in the same way as the
Telatar-Tse noisy two-pair interference channel generalizes the El Gamal-Costa
injective channel. Specifically, arbitrary noise is introduced that acts on the
combined interference signal before it affects the desired signal. This class
of channels includes the Gaussian case.
The rate region includes the best-known inner bound on the 3-DIC capacity
region, dominates treating interference as noise, and subsumes the
Han-Kobayashi region for the two-pair case.
|
1205.4785
|
Energy-Efficient Relaying over Multiple Slots with Causal CSI
|
cs.IT math.IT
|
In many communication scenarios, such as in cellular systems, the energy cost
is substantial and should be conserved, yet there is a growing need to support
many real-time applications that require timely data delivery. To model such a
scenario, in this paper we consider the problem of minimizing the expected sum
energy of delivering a message of a given size from a source to a destination
subject to a deadline constraint. A relay is present and can assist after it
has decoded the message. Causal channel state information (CSI), in the form of
present and past SNRs of all links, is available for determining the optimal
power allocation for the source and relay. We obtain the optimal power
allocation policy by dynamic programming and explore its structure. We also
obtain conditions for which the minimum expected sum energy is bounded given a
general channel distribution. In particular, we show that for Rayleigh and
Rician fading channels, relaying is necessary for the minimum expected sum
energy to be bounded. This illustrates the fundamental advantage of relaying
from the perspective of energy efficient communications when only causal CSI is
available. Numerical results are obtained which show the reduction in the
expected sum energy under different communication scenarios.
|
1205.4808
|
Importance of individual events in temporal networks
|
physics.soc-ph cond-mat.stat-mech cs.SI
|
Records of time-stamped social interactions between pairs of individuals
(e.g., face-to-face conversations, e-mail exchanges, and phone calls)
constitute a so-called temporal network. A remarkable difference between
temporal networks and conventional static networks is that time-stamped events
rather than links are the unit elements generating the collective behavior of
nodes. We propose an importance measure for single interaction events. By
generalizing the concept of the advance of event proposed by [Kossinets G,
Kleinberg J, and Watts D J (2008) Proceeding of the 14th ACM SIGKDD
International conference on knowledge discovery and data mining, p 435], we
propose that an event is central when it carries new information about others
to the two nodes involved in the event. We find that the proposed measure
properly quantifies the importance of events in connecting nodes along
time-ordered paths. Because of strong heterogeneity in the importance of events
present in real data, a small fraction of highly important events is necessary
and sufficient to sustain the connectivity of temporal networks. Nevertheless,
in contrast to the behavior of scale-free networks against link removal, this
property mainly results from bursty activity patterns and not heterogeneous
degree distributions.
|
1205.4810
|
Safe Exploration in Markov Decision Processes
|
cs.LG
|
In environments with uncertain dynamics exploration is necessary to learn how
to perform well. Existing reinforcement learning algorithms provide strong
exploration guarantees, but they tend to rely on an ergodicity assumption. The
essence of ergodicity is that any state is eventually reachable from any other
state by following a suitable policy. This assumption allows for exploration
algorithms that operate by simply favoring states that have rarely been visited
before. For most physical systems this assumption is impractical as the systems
would break before any reasonable exploration has taken place, i.e., most
physical systems don't satisfy the ergodicity assumption. In this paper we
address the need for safe exploration methods in Markov decision processes. We
first propose a general formulation of safety through ergodicity. We show that
imposing safety by restricting attention to the resulting set of guaranteed
safe policies is NP-hard. We then present an efficient algorithm for guaranteed
safe, but potentially suboptimal, exploration. At the core is an optimization
formulation in which the constraints restrict attention to a subset of the
guaranteed safe policies and the objective favors exploration policies. Our
framework is compatible with the majority of previously proposed exploration
methods, which rely on an exploration bonus. Our experiments, which include a
Martian terrain exploration problem, show that our method is able to explore
better than classical exploration methods.
|
1205.4813
|
Securing SQLJ Source Codes from Business Logic Disclosure by Data Hiding
Obfuscation
|
cs.CR cs.DB cs.DC
|
Information security is protecting information from unauthorized access, use,
disclosure, disruption, modification, perusal and destruction. CAIN model
suggest maintaining the Confidentiality, Authenticity, Integrity and
Non-repudiation (CAIN) of information. Oracle 8i, 9i and 11g Databases support
SQLJ framework allowing embedding of SQL statements in Java Programs and
providing programmer friendly means to access the Oracle database. As cloud
computing technology is becoming popular, SQLJ is considered as a flexible and
user friendly language for developing distributed applications in grid
architectures. SQLJ source codes are translated to java byte codes and
decompilation is generation of source codes from intermediate byte codes. The
intermediate SQLJ application byte codes are open to decompilation, allowing a
malicious reader to forcefully decompile it for understanding confidential
business logic or data from the codes. To the best of our knowledge, strong and
cost effective techniques exist for Oracle Database security, but still data
security techniques are lacking for client side applications, giving
possibility for revelation of confidential business data. Data obfuscation is
hiding the data in codes and we suggest enhancing the data security in SQLJ
source codes by data hiding, to mitigate disclosure of confidential business
data, especially integers in distributed applications.
|
1205.4831
|
Gray Level Co-Occurrence Matrices: Generalisation and Some New Features
|
cs.CV
|
Gray Level Co-occurrence Matrices (GLCM) are one of the earliest techniques
used for image texture analysis. In this paper we defined a new feature called
trace extracted from the GLCM and its implications in texture analysis are
discussed in the context of Content Based Image Retrieval (CBIR). The
theoretical extension of GLCM to n-dimensional gray scale images are also
discussed. The results indicate that trace features outperform Haralick
features when applied to CBIR.
|
1205.4839
|
Off-Policy Actor-Critic
|
cs.LG
|
This paper presents the first actor-critic algorithm for off-policy
reinforcement learning. Our algorithm is online and incremental, and its
per-time-step complexity scales linearly with the number of learned weights.
Previous work on actor-critic algorithms is limited to the on-policy setting
and does not take advantage of the recent advances in off-policy gradient
temporal-difference learning. Off-policy techniques, such as Greedy-GQ, enable
a target policy to be learned while following and obtaining data from another
(behavior) policy. For many problems, however, actor-critic methods are more
practical than action value methods (like Greedy-GQ) because they explicitly
represent the policy; consequently, the policy can be stochastic and utilize a
large action space. In this paper, we illustrate how to practically combine the
generality and learning potential of off-policy learning with the flexibility
in action selection given by actor-critic methods. We derive an incremental,
linear time and space complexity algorithm that includes eligibility traces,
prove convergence under assumptions similar to previous off-policy algorithms,
and empirically show better or comparable performance to existing algorithms on
standard reinforcement-learning benchmark problems.
|
1205.4856
|
Bounds on Minimum Number of Anchors for Iterative Localization and its
Connections to Bootstrap Percolation
|
cs.IT cs.NI math.IT math.PR
|
Iterated localization is considered where each node of a network needs to get
localized (find its location on 2-D plane), when initially only a subset of
nodes have their location information. The iterated localization process
proceeds as follows. Starting with a subset of nodes that have their location
information, possibly using global positioning system (GPS) devices, any other
node gets localized if it has three or more localized nodes in its radio range.
The newly localized nodes are included in the subset of nodes that have their
location information for the next iteration. This process is allowed to
continue, until no new node can be localized. The problem is to find the
minimum size of the initially localized subset to start with so that the whole
network is localized with high probability. There are intimate connections
between iterated localization and bootstrap percolation, that is well studied
in statistical physics. Using results known in bootstrap percolation, we find a
sufficient condition on the size of the initially localized subset that
guarantees the localization of all nodes in the network with high probability.
|
1205.4874
|
Perfect Secrecy Systems Immune to Spoofing Attacks
|
cs.CR cs.IT math.IT
|
We present novel perfect secrecy systems that provide immunity to spoofing
attacks under equiprobable source probability distributions. On the theoretical
side, relying on an existence result for $t$-designs by Teirlinck, our
construction method constructively generates systems that can reach an
arbitrary high level of security. On the practical side, we obtain, via cyclic
difference families, very efficient constructions of new optimal systems that
are onefold secure against spoofing. Moreover, we construct, by means of
$t$-designs for large values of $t$, the first near-optimal systems that are 5-
and 6-fold secure as well as further systems with a feasible number of keys
that are 7-fold secure against spoofing. We apply our results furthermore to a
recently extended authentication model, where the opponent has access to a
verification oracle. We obtain this way novel perfect secrecy systems with
immunity to spoofing in the verification oracle model.
|
1205.4875
|
A New Approach Towards the Golomb-Welch Conjecture
|
cs.IT math.IT
|
The Golomb-Welch conjecture deals with the existence of perfect $e$% -error
correcting Lee codes of word length $n,$ $PL(n,e)$ codes. Although there are
many papers on the topic, the conjecture is still far from being solved. In
this paper we initiate the study of an invariant connected to abelian groups
that enables us to reformulate the conjecture, and then to prove the
non-existence of linear PL(n,2) codes for $n\leq 12$. Using this new approach
we also construct the first quasi-perfect Lee codes for dimension $n=3,$ and
show that, for fixed $n$, there are only finitely many such codes over $Z^n$.
|
1205.4876
|
Selective Coding Strategy for Unicast Composite Networks
|
cs.IT math.IT
|
Consider a composite unicast relay network where the channel statistic is
randomly drawn from a set of conditional distributions indexed by a random
variable, which is assumed to be unknown at the source, fully known at the
destination and only partly known at the relays. Commonly, the coding strategy
at each relay is fixed regardless of its channel measurement. A novel coding
for unicast composite networks with multiple relays is introduced. This enables
the relays to select dynamically --based on its channel measurement-- the best
coding scheme between compress-and-forward (CF) and decode-and-forward (DF). As
a part of the main result, a generalization of Noisy Network Coding is shown
for the case of unicast general networks where the relays are divided between
those using DF and CF coding. Furthermore, the relays using DF scheme can
exploit the help of those based on CF scheme via offset coding. It is
demonstrated via numerical results that this novel coding, referred to as
Selective Coding Strategy (SCS), outperforms conventional coding schemes.
|
1205.4891
|
Clustering is difficult only when it does not matter
|
cs.LG cs.DS
|
Numerous papers ask how difficult it is to cluster data. We suggest that the
more relevant and interesting question is how difficult it is to cluster data
sets {\em that can be clustered well}. More generally, despite the ubiquity and
the great importance of clustering, we still do not have a satisfactory
mathematical theory of clustering. In order to properly understand clustering,
it is clearly necessary to develop a solid theoretical basis for the area. For
example, from the perspective of computational complexity theory the clustering
problem seems very hard. Numerous papers introduce various criteria and
numerical measures to quantify the quality of a given clustering. The resulting
conclusions are pessimistic, since it is computationally difficult to find an
optimal clustering of a given data set, if we go by any of these popular
criteria. In contrast, the practitioners' perspective is much more optimistic.
Our explanation for this disparity of opinions is that complexity theory
concentrates on the worst case, whereas in reality we only care for data sets
that can be clustered well.
We introduce a theoretical framework of clustering in metric spaces that
revolves around a notion of "good clustering". We show that if a good
clustering exists, then in many cases it can be efficiently found. Our
conclusion is that contrary to popular belief, clustering should not be
considered a hard task.
|
1205.4893
|
On the practically interesting instances of MAXCUT
|
cs.CC cs.LG
|
The complexity of a computational problem is traditionally quantified based
on the hardness of its worst case. This approach has many advantages and has
led to a deep and beautiful theory. However, from the practical perspective,
this leaves much to be desired. In application areas, practically interesting
instances very often occupy just a tiny part of an algorithm's space of
instances, and the vast majority of instances are simply irrelevant. Addressing
these issues is a major challenge for theoretical computer science which may
make theory more relevant to the practice of computer science.
Following Bilu and Linial, we apply this perspective to MAXCUT, viewed as a
clustering problem. Using a variety of techniques, we investigate practically
interesting instances of this problem. Specifically, we show how to solve in
polynomial time distinguished, metric, expanding and dense instances of MAXCUT
under mild stability assumptions. In particular, $(1+\epsilon)$-stability
(which is optimal) suffices for metric and dense MAXCUT. We also show how to
solve in polynomial time $\Omega(\sqrt{n})$-stable instances of MAXCUT,
substantially improving the best previously known result.
|
1205.4894
|
Effective and efficient approximations of the generalized inverse of the
graph Laplacian matrix with an application to current-flow betweenness
centrality
|
cs.SI physics.soc-ph
|
We devise methods for finding approximations of the generalized inverse of
the graph Laplacian matrix, which arises in many graph-theoretic applications.
Finding this matrix in its entirety involves solving a matrix inversion
problem, which is resource demanding in terms of consumed time and memory and
hence impractical whenever the graph is relatively large. Our approximations
use only few eigenpairs of the Laplacian matrix and are parametric with respect
to this number, so that the user can compromise between effectiveness and
efficiency of the approximated solution. We apply the devised approximations to
the problem of computing current-flow betweenness centrality on a graph.
However, given the generality of the Laplacian matrix, many other applications
can be sought. We experimentally demonstrate that the approximations are
effective already with a constant number of eigenpairs. These few eigenpairs
can be stored with a linear amount of memory in the number of nodes of the
graph and, in the realistic case of sparse networks, they can be efficiently
computed using one of the many methods for retrieving few eigenpairs of sparse
matrices that abound in the literature.
|
1205.4933
|
Compressed Sensing on the Image of Bilinear Maps
|
cs.IT math.IT
|
For several communication models, the dispersive part of a communication
channel is described by a bilinear operation $T$ between the possible sets of
input signals and channel parameters. The received channel output has then to
be identified from the image $T(X,Y)$ of the input signal difference sets $X$
and the channel state sets $Y$. The main goal in this contribution is to
characterize the compressibility of $T(X,Y)$ with respect to an ambient
dimension $N$. In this paper we show that a restricted norm multiplicativity of
$T$ on all canonical subspaces $X$ and $Y$ with dimension $S$ resp. $F$ is
sufficient for the reconstruction of output signals with an overwhelming
probability from $\mathcal{O}((S+F)\log N)$ random sub-Gaussian measurements.
|
1205.4971
|
Data Gathering in Networks of Bacteria Colonies: Collective Sensing and
Relaying Using Molecular Communication
|
cs.IT math.IT q-bio.MN
|
The prospect of new biological and industrial applications that require
communication in micro-scale, encourages research on the design of
bio-compatible communication networks using networking primitives already
available in nature. One of the most promising candidates for constructing such
networks is to adapt and engineer specific types of bacteria that are capable
of sensing, actuation, and above all, communication with each other. In this
paper, we describe a new architecture for networks of bacteria to form a data
collecting network, as in traditional sensor networks. The key to this
architecture is the fact that the node in the network itself is a bacterial
colony; as an individual bacterium (biological agent) is a tiny unreliable
element with limited capabilities. We describe such a network under two
different scenarios. We study the data gathering (sensing and multihop
communication) scenario as in sensor networks followed by the consensus problem
in a multi-node network. We will explain as to how the bacteria in the colony
collectively orchestrate their actions as a node to perform sensing and
relaying tasks that would not be possible (at least reliably) by an individual
bacterium. Each single bacterium in the colony forms a belief by sensing
external parameter (e.g., a molecular signal from another node) from the medium
and shares its belief with other bacteria in the colony. Then, after some
interactions, all the bacteria in the colony form a common belief and act as a
single node. We will model the reception process of each individual bacteria
and will study its impact on the overall functionality of a node. We will
present results on the reliability of the multihop communication for data
gathering scenario as well as the speed of convergence in the consensus
scenario.
|
1205.4983
|
Collective Sensing-Capacity of Bacteria Populations
|
cs.IT math.IT
|
The design of biological networks using bacteria as the basic elements of the
network is initially motivated by a phenomenon called quorum sensing. Through
quorum sensing, each bacterium performs sensing the medium and communicating it
to others via molecular communication. As a result, bacteria can orchestrate
and act collectively and perform tasks impossible otherwise. In this paper, we
consider a population of bacteria as a single node in a network. In our version
of biological communication networks, such a node would communicate with one
another via molecular signals. As a first step toward such networks, this paper
focuses on the study of the transfer of information to the population (i.e.,
the node) by stimulating it with a concentration of special type of a molecules
signal. These molecules trigger a chain of processes inside each bacteria that
results in a final output in the form of light or fluorescence. Each stage in
the process adds noise to the signal carried to the next stage. Our objective
is to measure (compute) the maximum amount of information that we can transfer
to the node. This can be viewed as the collective sensing capacity of the node.
The molecular concentration, which carries the information, is the input to the
node, which should be estimated by observing the produced light as the output
of the node (i.e., the entire population of bacteria forming the node). We
focus on the noise caused by the random process of trapping molecules at the
receptors as well as the variation of outputs of different bacteria in the
node. The capacity variation with the number of bacteria in the node and the
number of receptors per bacteria is obtained. Finally, we investigated the
collective sensing capability of the node when a specific form of molecular
signaling concentration is used.
|
1205.4988
|
Capacity of Diffusion-based Molecular Communication with Ligand
Receptors
|
cs.IT math.IT
|
A diffusion-based molecular communication system has two major components:
the diffusion in the medium, and the ligand-reception. Information bits,
encoded in the time variations of the concentration of molecules, are conveyed
to the receiver front through the molecular diffusion in the medium. The
receiver, in turn, measures the concentration of the molecules in its vicinity
in order to retrieve the information. This is done via ligand-reception
process. In this paper, we develop models to study the constraints imposed by
the concentration sensing at the receiver side and derive the maximum rate by
which a ligand-receiver can receive information. Therefore, the overall
capacity of the diffusion channel with the ligand receptors can be obtained by
combining the results presented in this paper with our previous work on the
achievable information rate of molecular communication over the diffusion
channel.
|
1205.4996
|
Ber analysis of iterative turbo encoded miso wireless communication
system under implementation of q-ostbc scheme
|
cs.IT math.IT
|
In this paper, a comprehensive study has been made to evaluate the
performance of a MISO wireless communication system. The 4-by-1 spatially
multiplexed Turbo encoded system under investigation incorporates
Quasi-orthogonal space-time block coding (Q-STBC) and ML signal detection
schemes under QPSK, QAM, 16PSK and 16QAM digital modulations. The simulation
results elucidate that a significant improvement of system performance is
achieved in QAM modulation. The results are also indicative of noticeable
system performance enhancement with increasing number of iterations in Turbo
encoding/decoding scheme.
|
1205.5003
|
Ring Exploration with Oblivious Myopic Robots
|
cs.MA cs.DC
|
The exploration problem in the discrete universe, using identical oblivious
asynchronous robots without direct communication, has been well investigated.
These robots have sensors that allow them to see their environment and move
accordingly. However, the previous work on this problem assume that robots have
an unlimited visibility, that is, they can see the position of all the other
robots. In this paper, we consider deterministic exploration in an anonymous,
unoriented ring using asynchronous, oblivious, and myopic robots. By myopic, we
mean that the robots have only a limited visibility. We study the computational
limits imposed by such robots and we show that under some conditions the
exploration problem can still be solved. We study the cases where the robots
visibility is limited to 1, 2, and 3 neighboring nodes, respectively.
|
1205.5004
|
Systematic DFT Frames: Principle and Eigenvalues Structure
|
cs.IT math.IT
|
Motivated by a host of recent applications requiring some amount of
redundancy, frames are becoming a standard tool in the signal processing
toolbox. In this paper, we study a specific class of frames, known as discrete
Fourier transform (DFT) codes, and introduce the notion of systematic frames
for this class. This is encouraged by application of systematic DFT codes in
distributed source coding using DFT codes, a new application for frames.
Studying their extreme eigenvalues, we show that, unlike DFT frames, systematic
DFT frames are not necessarily tight. Then, we come up with conditions for
which these frames can be tight. In either case, the best and worst systematic
frames are established from reconstruction error point of view. Eigenvalues of
DFT frames, and their subframes, play a pivotal role in this work.
|
1205.5012
|
Learning Mixed Graphical Models
|
stat.ML cs.CV cs.LG math.OC
|
We consider the problem of learning the structure of a pairwise graphical
model over continuous and discrete variables. We present a new pairwise model
for graphical models with both continuous and discrete variables that is
amenable to structure learning. In previous work, authors have considered
structure learning of Gaussian graphical models and structure learning of
discrete models. Our approach is a natural generalization of these two lines of
work to the mixed case. The penalization scheme involves a novel symmetric use
of the group-lasso norm and follows naturally from a particular parametrization
of the model.
|
1205.5024
|
Analytical Study of Hexapod miRNAs using Phylogenetic Methods
|
cs.CE q-bio.GN
|
MicroRNAs (miRNAs) are a class of non-coding RNAs that regulate gene
expression. Identification of total number of miRNAs even in completely
sequenced organisms is still an open problem. However, researchers have been
using techniques that can predict limited number of miRNA in an organism. In
this paper, we have used homology based approach for comparative analysis of
miRNA of hexapoda group .We have used Apis mellifera, Bombyx mori, Anopholes
gambiae and Drosophila melanogaster miRNA datasets from miRBase repository. We
have done pair wise as well as multiple alignments for the available miRNAs in
the repository to identify and analyse conserved regions among related species.
Unfortunately, to the best of our knowledge, miRNA related literature does not
provide in depth analysis of hexapods. We have made an attempt to derive the
commonality among the miRNAs and to identify the conserved regions which are
still not available in miRNA repositories. The results are good approximation
with a small number of mismatches. However, they are encouraging and may
facilitate miRNA biogenesis for
|
1205.5025
|
FragIt: A Tool to Prepare Input Files for Fragment Based Quantum
Chemical Calculations
|
cs.CE physics.chem-ph
|
Near linear scaling fragment based quantum chemical calculations are becoming
increasingly popular for treating large systems with high accuracy and is an
active field of research. However, it remains difficult to set up these
calculations without expert knowledge. To facilitate the use of such methods,
software tools need to be available to support these methods and help to set up
reasonable input files which will lower the barrier of entry for usage by
non-experts. Previous tools relies on specific annotations in structure files
for automatic and successful fragmentation such as residues in PDB files. We
present a general fragmentation methodology and accompanying tools called
FragIt to help setup these calculations. FragIt uses the SMARTS language to
locate chemically appropriate fragments in large structures and is applicable
to fragmentation of any molecular system given suitable SMARTS patterns. We
present SMARTS patterns of fragmentation for proteins, DNA and polysaccharides,
specifically for D-galactopyranose for use in cyclodextrins. FragIt is used to
prepare input files for the Fragment Molecular Orbital method in the GAMESS
program package, but can be extended to other computational methods easily.
|
1205.5062
|
The Classification of Complementary Information Set Codes of Lengths 14
and 16
|
cs.IT math.IT
|
In the paper "A new class of codes for Boolean masking of cryptographic
computations," Carlet, Gaborit, Kim, and Sol\'{e} defined a new class of rate
one-half binary codes called \emph{complementary information set} (or CIS)
codes. The authors then classified all CIS codes of length less than or equal
to 12. CIS codes have relations to classical Coding Theory as they are a
generalization of self-dual codes. As stated in the paper, CIS codes also have
important practical applications as they may improve the cost of masking
cryptographic algorithms against side channel attacks. In this paper, we give a
complete classification result for length 14 CIS codes using an equivalence
relation on $GL(n,\FF_2)$. We also give a new classification for all binary
$[16,8,3]$ and $[16,8,4]$ codes. We then complete the classification for length
16 CIS codes and give additional classifications for optimal CIS codes of
lengths 20 and 26.
|
1205.5073
|
Secure estimation and control for cyber-physical systems under
adversarial attacks
|
math.OC cs.CR cs.IT cs.SY math.IT
|
The vast majority of today's critical infrastructure is supported by numerous
feedback control loops and an attack on these control loops can have disastrous
consequences. This is a major concern since modern control systems are becoming
large and decentralized and thus more vulnerable to attacks. This paper is
concerned with the estimation and control of linear systems when some of the
sensors or actuators are corrupted by an attacker. In the first part we look at
the estimation problem where we characterize the resilience of a system to
attacks and study the possibility of increasing its resilience by a change of
parameters. We then propose an efficient algorithm to estimate the state
despite the attacks and we characterize its performance. Our approach is
inspired from the areas of error-correction over the reals and compressed
sensing. In the second part we consider the problem of designing
output-feedback controllers that stabilize the system despite attacks. We show
that a principle of separation between estimation and control holds and that
the design of resilient output feedback controllers can be reduced to the
design of resilient state estimators.
|
1205.5075
|
Efficient Sparse Group Feature Selection via Nonconvex Optimization
|
cs.LG stat.ML
|
Sparse feature selection has been demonstrated to be effective in handling
high-dimensional data. While promising, most of the existing works use convex
methods, which may be suboptimal in terms of the accuracy of feature selection
and parameter estimation. In this paper, we expand a nonconvex paradigm to
sparse group feature selection, which is motivated by applications that require
identifying the underlying group structure and performing feature selection
simultaneously. The main contributions of this article are twofold: (1)
statistically, we introduce a nonconvex sparse group feature selection model
which can reconstruct the oracle estimator. Therefore, consistent feature
selection and parameter estimation can be achieved; (2) computationally, we
propose an efficient algorithm that is applicable to large-scale problems.
Numerical results suggest that the proposed nonconvex method compares favorably
against its competitors on synthetic data and real-world applications, thus
achieving desired goal of delivering high performance.
|
1205.5088
|
Kinodynamic RRT*: Optimal Motion Planning for Systems with Linear
Differential Constraints
|
cs.RO cs.DS
|
We present Kinodynamic RRT*, an incremental sampling-based approach for
asymptotically optimal motion planning for robots with linear differential
constraints. Our approach extends RRT*, which was introduced for holonomic
robots (Karaman et al. 2011), by using a fixed-final-state-free-final-time
controller that exactly and optimally connects any pair of states, where the
cost function is expressed as a trade-off between the duration of a trajectory
and the expended control effort. Our approach generalizes earlier work on
extending RRT* to kinodynamic systems, as it guarantees asymptotic optimality
for any system with controllable linear dynamics, in state spaces of any
dimension. Our approach can be applied to non-linear dynamics as well by using
their first-order Taylor approximations. In addition, we show that for the rich
subclass of systems with a nilpotent dynamics matrix, closed-form solutions for
optimal trajectories can be derived, which keeps the computational overhead of
our algorithm compared to traditional RRT* at a minimum. We demonstrate the
potential of our approach by computing asymptotically optimal trajectories in
three challenging motion planning scenarios: (i) a planar robot with a 4-D
state space and double integrator dynamics, (ii) an aerial vehicle with a 10-D
state space and linearized quadrotor dynamics, and (iii) a car-like robot with
a 5-D state space and non-linear dynamics.
|
1205.5097
|
Neural Network Approach for Eye Detection
|
cs.CV
|
Driving support systems, such as car navigation systems are becoming common
and they support driver in several aspects. Non-intrusive method of detecting
Fatigue and drowsiness based on eye-blink count and eye directed instruction
controlhelps the driver to prevent from collision caused by drowsy driving. Eye
detection and tracking under various conditions such as illumination,
background, face alignment and facial expression makes the problem
complex.Neural Network based algorithm is proposed in this paper to detect the
eyes efficiently. In the proposed algorithm, first the neural Network is
trained to reject the non-eye regionbased on images with features of eyes and
the images with features of non-eye using Gabor filter and Support Vector
Machines to reduce the dimension and classify efficiently. In the algorithm,
first the face is segmented using L*a*btransform color space, then eyes are
detected using HSV and Neural Network approach. The algorithm is tested on
nearly 100 images of different persons under different conditions and the
results are satisfactory with success rate of 98%.The Neural Network is trained
with 50 non-eye images and 50 eye images with different angles using Gabor
filter. This paper is a part of research work on "Development of Non-Intrusive
system for real-time Monitoring and Prediction of Driver Fatigue and
drowsiness" project sponsored by Department of Science & Technology, Govt. of
India, New Delhi at Vignan Institute of Technology and Sciences, Vignan Hills,
Hyderabad.
|
1205.5098
|
A Simplified Description of Fuzzy TOPSIS
|
cs.AI
|
A simplified description of Fuzzy TOPSIS (Technique for Order Preference by
Similarity to Ideal Situation) is presented. We have adapted the TOPSIS
description from existing Fuzzy theory literature and distilled the bare
minimum concepts required for understanding and applying TOPSIS. An example has
been worked out to illustrate the application of TOPSIS for a multi-criteria
group decision making scenario.
|
1205.5109
|
Self-exciting point process modeling of conversation event sequences
|
physics.soc-ph cs.SI
|
Self-exciting processes of Hawkes type have been used to model various
phenomena including earthquakes, neural activities, and views of online videos.
Studies of temporal networks have revealed that sequences of social interevent
times for individuals are highly bursty. We examine some basic properties of
event sequences generated by the Hawkes self-exciting process to show that it
generates bursty interevent times for a wide parameter range. Then, we fit the
model to the data of conversation sequences recorded in company offices in
Japan. In this way, we can estimate relative magnitudes of the self excitement,
its temporal decay, and the base event rate independent of the self excitation.
These variables highly depend on individuals. We also point out that the Hawkes
model has an important limitation that the correlation in the interevent times
and the burstiness cannot be independently modulated.
|
1205.5124
|
Interference and Throughput in Aloha-based Ad Hoc Networks with
Isotropic Node Distribution
|
cs.IT math.IT
|
We study the interference and outage statistics in a slotted Aloha ad hoc
network, where the spatial distribution of nodes is non-stationary and
isotropic. In such a network, outage probability and local throughput depend on
both the particular location in the network and the shape of the spatial
distribution. We derive in closed-form certain distributional properties of the
interference that are important for analyzing wireless networks as a function
of the location and the spatial shape. Our results focus on path loss exponents
2 and 4, the former case not being analyzable before due to the stationarity
assumption of the spatial node distribution. We propose two metrics for
measuring local throughput in non-stationary networks and discuss how our
findings can be applied to both analysis and optimization.
|
1205.5134
|
Iterated Space-Time Code Constructions from Cyclic Algebras
|
cs.IT math.IT math.RA
|
We propose a full-rate iterated space-time code construction, to design
2n-dimensional codes from n-dimensional cyclic algebra based codes. We give a
condition to determine whether the resulting codes satisfy the full-diversity
property, and study their maximum likelihood decoding complexity with respect
to sphere decoding. Particular emphasis is given to the cases n = 2, sometimes
referred to as MIDO (multiple input double output) codes, and n = 3. In the
process, we derive an interesting way of obtaining division algebras, and study
their center and maximal subfield.
|
1205.5141
|
There is no [21, 5, 14] code over F5
|
math.CO cs.IT math.IT
|
In this note, we demonstrate that there is no [21, 5, 14] code over F5.
|
1205.5148
|
On Burst Error Correction and Storage Security of Noisy Data
|
cs.IT cs.CR math.IT
|
Secure storage of noisy data for authentication purposes usually involves the
use of error correcting codes. We propose a new model scenario involving burst
errors and present for that several constructions.
|
1205.5263
|
Pebble Motion on Graphs with Rotations: Efficient Feasibility Tests and
Planning Algorithms
|
cs.DS cs.RO
|
We study the problem of planning paths for $p$ distinguishable pebbles
(robots) residing on the vertices of an $n$-vertex connected graph with $p \le
n$. A pebble may move from a vertex to an adjacent one in a time step provided
that it does not collide with other pebbles. When $p = n$, the only collision
free moves are synchronous rotations of pebbles on disjoint cycles of the
graph. We show that the feasibility of such problems is intrinsically
determined by the diameter of a (unique) permutation group induced by the
underlying graph. Roughly speaking, the diameter of a group $\mathbf G$ is the
minimum length of the generator product required to reach an arbitrary element
of $\mathbf G$ from the identity element. Through bounding the diameter of this
associated permutation group, which assumes a maximum value of $O(n^2)$, we
establish a linear time algorithm for deciding the feasibility of such problems
and an $O(n^3)$ algorithm for planning complete paths.
|
1205.5297
|
Non-nequilibrium model on Apollonian networks
|
physics.soc-ph cs.SI
|
We investigate the Majority-Vote Model with two states ($-1,+1$) and a noise
$q$ on Apollonian networks. The main result found here is the presence of the
phase transition as a function of the noise parameter $q$. We also studies de
effect of redirecting a fraction $p$ of the links of the network. By means of
Monte Carlo simulations, we obtained the exponent ratio $\gamma/\nu$,
$\beta/\nu$, and $1/\nu$ for several values of rewiring probability $p$. The
critical noise was determined $q_{c}$ and $U^{*}$ also was calculated. The
effective dimensionality of the system was observed to be independent on $p$,
and the value $D_{eff} \approx1.0$ is observed for these networks. Previous
results on the Ising model in Apollonian Networks have reported no presence of
a phase transition. Therefore, the results present here demonstrate that the
Majority-Vote Model belongs to a different universality class as the
equilibrium Ising Model on Apollonian Network.
|
1205.5324
|
Linear Network Code for Erasure Broadcast Channel with Feedback:
Complexity and Algorithms
|
cs.IT cs.CC math.IT
|
This paper investigates the construction of linear network codes for
broadcasting a set of data packets to a number of users. The links from the
source to the users are modeled as independent erasure channels. Users are
allowed to inform the source node whether a packet is received correctly via
feedback channels. In order to minimize the number of packet transmissions
until all users have received all packets successfully, it is necessary that a
data packet, if successfully received by a user, can increase the dimension of
the vector space spanned by the encoding vectors he or she has received by one.
Such an encoding vector is called innovative. We prove that innovative linear
network code is uniformly optimal in minimizing user download delay. When the
finite field size is strictly smaller than the number of users, the problem of
determining the existence of innovative vectors is proven to be NP-complete.
When the field size is larger than or equal to the number of users, innovative
vectors always exist and random linear network code (RLNC) is able to find an
innovative vector with high probability. While RLNC is optimal in terms of
completion time, it has high decoding complexity due to the need of solving a
system of linear equations. To reduce decoding time, we propose the use of
sparse linear network code, since the sparsity property of encoding vectors can
be exploited when solving systems of linear equations. Generating a sparsest
encoding vector with large finite field size, however, is shown to be NP-hard.
An approximation algorithm that guarantee the Hamming weight of a generated
encoding vector to be smaller than a certain factor of the optimal value is
constructed. Our simulation results show that our proposed methods have
excellent performance in completion time and outperforms RLNC in terms of
decoding time.
|
1205.5341
|
Joint Channel Estimation and Data Detection for Multihop OFDM Relaying
System under Unknown Channel Orders and Doppler Frequencies
|
cs.IT math.IT
|
In this paper, channel estimation and data detection for multihop relaying
orthogonal frequency division multiplexing (OFDM) system is investigated under
time-varying channel. Different from previous works, which highly depend on the
statistical information of the doubly-selective channel (DSC) and noise to
deliver accurate channel estimation and data detection results, we focus on
more practical scenarios with unknown channel orders and Doppler frequencies.
Firstly, we integrate the multilink, multihop channel matrices into one
composite channel matrix. Then, we formulate the unknown channel using
generalized complex exponential basis expansion model (GCE-BEM) with a large
oversampling factor to introduce channel sparsity on delay-Doppler domain. To
enable the identification of nonzero entries, sparsity enhancing Gaussian
distributions with Gamma hyperpriors are adopted. An iterative algorithm is
developed under variational inference (VI) framework. The proposed algorithm
iteratively estimate the channel, recover the unknown data using Viterbi
algorithm and learn the channel and noise statistical information, using only
limited number of pilot subcarrier in one OFDM symbol. Simulation results show
that, without any statistical information, the performance of the proposed
algorithm is very close to that of the optimal channel estimation and data
detection algorithm, which requires specific information on system structure,
channel tap positions, channel lengths, Doppler shifts as well as noise powers.
|
1205.5351
|
Linearized Alternating Direction Method with Adaptive Penalty and Warm
Starts for Fast Solving Transform Invariant Low-Rank Textures
|
cs.CV
|
Transform Invariant Low-rank Textures (TILT) is a novel and powerful tool
that can effectively rectify a rich class of low-rank textures in 3D scenes
from 2D images despite significant deformation and corruption. The existing
algorithm for solving TILT is based on the alternating direction method (ADM).
It suffers from high computational cost and is not theoretically guaranteed to
converge to a correct solution. In this paper, we propose a novel algorithm to
speed up solving TILT, with guaranteed convergence. Our method is based on the
recently proposed linearized alternating direction method with adaptive penalty
(LADMAP). To further reduce computation, warm starts are also introduced to
initialize the variables better and cut the cost on singular value
decomposition. Extensive experimental results on both synthetic and real data
demonstrate that this new algorithm works much more efficiently and robustly
than the existing algorithm. It could be at least five times faster than the
previous method.
|
1205.5353
|
A hybrid clustering algorithm for data mining
|
cs.DB cs.LG
|
Data clustering is a process of arranging similar data into groups. A
clustering algorithm partitions a data set into several groups such that the
similarity within a group is better than among groups. In this paper a hybrid
clustering algorithm based on K-mean and K-harmonic mean (KHM) is described.
The proposed algorithm is tested on five different datasets. The research is
focused on fast and accurate clustering. Its performance is compared with the
traditional K-means & KHM algorithm. The result obtained from proposed hybrid
algorithm is much better than the traditional K-mean & KHM algorithm.
|
1205.5367
|
Language-Constraint Reachability Learning in Probabilistic Graphs
|
cs.AI cs.LG
|
The probabilistic graphs framework models the uncertainty inherent in
real-world domains by means of probabilistic edges whose value quantifies the
likelihood of the edge existence or the strength of the link it represents. The
goal of this paper is to provide a learning method to compute the most likely
relationship between two nodes in a framework based on probabilistic graphs. In
particular, given a probabilistic graph we adopted the language-constraint
reachability method to compute the probability of possible interconnections
that may exists between two nodes. Each of these connections may be viewed as
feature, or a factor, between the two nodes and the corresponding probability
as its weight. Each observed link is considered as a positive instance for its
corresponding link label. Given the training set of observed links a
L2-regularized Logistic Regression has been adopted to learn a model able to
predict unobserved link labels. The experiments on a real world collaborative
filtering problem proved that the proposed approach achieves better results
than that obtained adopting classical methods.
|
1205.5375
|
On Optimality of Myopic Policy for Restless Multi-armed Bandit Problem
with Non i.i.d. Arms and Imperfect Detection
|
cs.SY cs.GT
|
We consider the channel access problem in a multi-channel opportunistic
communication system with imperfect channel sensing, where the state of each
channel evolves as a non independent and identically distributed Markov
process. This problem can be cast into a restless multi-armed bandit (RMAB)
problem that is intractable for its exponential computation complexity. A
natural alternative is to consider the easily implementable myopic policy that
maximizes the immediate reward but ignores the impact of the current strategy
on the future reward. In particular, we develop three axioms characterizing a
family of generic and practically important functions termed as $g$-regular
functions which includes a wide spectrum of utility functions in engineering.
By pursuing a mathematical analysis based on the axioms, we establish a set of
closed-form structural conditions for the optimality of myopic policy.
|
1205.5407
|
FASTSUBS: An Efficient and Exact Procedure for Finding the Most Likely
Lexical Substitutes Based on an N-gram Language Model
|
cs.CL
|
Lexical substitutes have found use in areas such as paraphrasing, text
simplification, machine translation, word sense disambiguation, and part of
speech induction. However the computational complexity of accurately
identifying the most likely substitutes for a word has made large scale
experiments difficult. In this paper I introduce a new search algorithm,
FASTSUBS, that is guaranteed to find the K most likely lexical substitutes for
a given word in a sentence based on an n-gram language model. The computation
is sub-linear in both K and the vocabulary size V. An implementation of the
algorithm and a dataset with the top 100 substitutes of each token in the WSJ
section of the Penn Treebank are available at http://goo.gl/jzKH0.
|
1205.5425
|
Locally Orderless Registration
|
cs.CV
|
Image registration is an important tool for medical image analysis and is
used to bring images into the same reference frame by warping the coordinate
field of one image, such that some similarity measure is minimized. We study
similarity in image registration in the context of Locally Orderless Images
(LOI), which is the natural way to study density estimates and reveals the 3
fundamental scales: the measurement scale, the intensity scale, and the
integration scale.
This paper has three main contributions: Firstly, we rephrase a large set of
popular similarity measures into a common framework, which we refer to as
Locally Orderless Registration, and which makes full use of the features of
local histograms. Secondly, we extend the theoretical understanding of the
local histograms. Thirdly, we use our framework to compare two state-of-the-art
intensity density estimators for image registration: The Parzen Window (PW) and
the Generalized Partial Volume (GPV), and we demonstrate their differences on a
popular similarity measure, Normalized Mutual Information (NMI).
We conclude, that complicated similarity measures such as NMI may be
evaluated almost as fast as simple measures such as Sum of Squared Distances
(SSD) regardless of the choice of PW and GPV. Also, GPV is an asymmetric
measure, and PW is our preferred choice.
|
1205.5443
|
Filter-and-Forward Transparent Relay Design for OFDM Systems
|
cs.IT math.IT
|
In this paper, the filter-and-forward (FF) relay design for orthogonal
frequency-division multiplexing (OFDM) transmission systems is considered to
improve the system performance over simple amplify-and-forward (AF) relaying.
Unlike conventional OFDM relays performing OFDM demodulation and remodulation,
to reduce processing complexity, the proposed FF relay directly filters the
incoming signal in time domain with a finite impulse response (FIR) and
forwards the filtered signal to the destination. Three design criteria are
considered to optimize the relay filter. The first criterion is the
minimization of the relay transmit power subject to per-subcarrier
signal-to-noise ratio (SNR) constraints, the second is the maximization of the
worst subcarrier channel SNR subject to source and relay transmit power
constraints, and the third is the maximization of data rate subject to source
and relay transmit power constraints. It is shown that the first problem
reduces to a semi-definite programming (SDP) problem by semi-definite
relaxation and the solution to the relaxed SDP problem has rank one under a
mild condition. For the latter two problems, the problem of joint source power
allocation and relay filter design is considered and an efficient algorithm is
proposed for each problem based on alternating optimization and the projected
gradient method (PGM). Numerical results show that the proposed FF relay
significantly outperforms simple AF relays with insignificant increase in
complexity. Thus, the proposed FF relay provides a practical alternative to the
AF relaying scheme for OFDM transmission.
|
1205.5465
|
Isometry and Automorphisms of Constant Dimension Codes
|
cs.IT math.IT
|
We define linear and semilinear isometry for general subspace codes, used for
random network coding. Furthermore, some results on isometry classes and
automorphism groups of known constant dimension code constructions are derived.
|
1205.5504
|
Algorithmic randomness and stochastic selection function
|
cs.IT math.IT
|
We show algorithmic randomness versions of the two classical theorems on
subsequences of normal numbers. One is Kamae-Weiss theorem (Kamae 1973) on
normal numbers, which characterize the selection function that preserves normal
numbers. Another one is the Steinhaus (1922) theorem on normal numbers, which
characterize the normality from their subsequences. In van Lambalgen (1987), an
algorithmic analogy to Kamae-Weiss theorem is conjectured in terms of
algorithmic randomness and complexity. In this paper we consider two types of
algorithmic random sequence; one is ML-random sequences and the other one is
the set of sequences that have maximal complexity rate. Then we show
algorithmic randomness versions of corresponding theorems to the above
classical results.
|
1205.5509
|
Four Degrees of Separation, Really
|
cs.SI physics.soc-ph
|
We recently measured the average distance of users in the Facebook graph,
spurring comments in the scientific community as well as in the general press
("Four Degrees of Separation"). A number of interesting criticisms have been
made about the meaningfulness, methods and consequences of the experiment we
performed. In this paper we want to discuss some methodological aspects that we
deem important to underline in the form of answers to the questions we have
read in newspapers, magazines, blogs, or heard from colleagues. We indulge in
some reflections on the actual meaning of "average distance" and make a number
of side observations showing that, yes, 3.74 "degrees of separation" are really
few.
|
1205.5522
|
The Capacity Loss of Dense Constellations
|
cs.IT math.IT
|
We determine the loss in capacity incurred by using signal constellations
with a bounded support over general complex-valued additive-noise channels for
suitably high signal-to-noise ratio. Our expression for the capacity loss
recovers the power loss of 1.53dB for square signal constellations.
|
1205.5569
|
A Theory of Information Matching
|
cs.IR
|
In this work, we propose a theory for information matching. It is motivated
by the observation that retrieval is about the relevance matching between two
sets of properties (features), namely, the information need representation and
information item representation. However, many probabilistic retrieval models
rely on fixing one representation and optimizing the other (e.g. fixing the
single information need and tuning the document) but not both. Therefore, it is
difficult to use the available related information on both the document and the
query at the same time in calculating the probability of relevance. In this
paper, we address the problem by hypothesizing the relevance as a logical
relationship between the two sets of properties; the relationship is defined on
two separate mappings between these properties. By using the hypothesis we
develop a unified probabilistic relevance model which is capable of using all
the available information. We validate the proposed theory by formulating and
developing probabilistic relevance ranking functions for both ad-hoc text
retrieval and collaborative filtering. Our derivation in text retrieval
illustrates the use of the theory in the situation where no relevance
information is available. In collaborative filtering, we show that the
resulting recommender model unifies the user and item information into a
relevance ranking function without applying any dimensionality reduction
techniques or computing explicit similarity between two different users (or
items), in contrast to the state-of-the-art recommender models.
|
1205.5589
|
Technical report: Two observations on probability distribution
symmetries for randomly-projected data
|
cs.IT math.IT
|
In this technical report, we will make two observations concerning symmetries
of the probability distribution resulting from projection of a piece of
p-dimensional data onto a random m-dimensional subspace of $\mathbb{R}^p$,
where m < p. In particular, we shall observe that such distributions are
unchanged by reflection across the original data vector and by rotation about
the original data vector
|
1205.5602
|
The Capacity Region of Restricted Multi-Way Relay Channels with
Deterministic Uplinks
|
cs.IT math.IT
|
This paper considers the multi-way relay channel (MWRC) where multiple users
exchange messages via a single relay. The capacity region is derived for a
special class of MWRCs where (i) the uplink and the downlink are separated in
the sense that there is no direct user-to-user links, (ii) the channel is
restricted in the sense that each user's transmitted channel symbols can depend
on only its own message, but not on its received channel symbols, and (iii) the
uplink is any deterministic function.
|
1205.5603
|
The Finite Field Multi-Way Relay Channel with Correlated Sources: Beyond
Three Users
|
cs.IT math.IT
|
The multi-way relay channel (MWRC) models cooperative communication networks
in which many users exchange messages via a relay. In this paper, we consider
the finite field MWRC with correlated messages. The problem is to find all
achievable rates, defined as the number of channel uses required per reliable
exchange of message tuple. For the case of three users, we have previously
established that for a special class of source distributions, the set of all
achievable rates can be found [Ong et al., ISIT 2010]. The class is specified
by an almost balanced conditional mutual information (ABCMI) condition. In this
paper, we first generalize the ABCMI condition to the case of more than three
users. We then show that if the sources satisfy the ABCMI condition, then the
set of all achievable rates is found and can be attained using a separate
source-channel coding architecture.
|
1205.5611
|
Beyond citations: Scholars' visibility on the social Web
|
cs.DL cs.SI physics.soc-ph
|
Traditionally, scholarly impact and visibility have been measured by counting
publications and citations in the scholarly literature. However, increasingly
scholars are also visible on the Web, establishing presences in a growing
variety of social ecosystems. But how wide and established is this presence,
and how do measures of social Web impact relate to their more traditional
counterparts? To answer this, we sampled 57 presenters from the 2010 Leiden STI
Conference, gathering publication and citations counts as well as data from the
presenters' Web "footprints." We found Web presence widespread and diverse: 84%
of scholars had homepages, 70% were on LinkedIn, 23% had public Google Scholar
profiles, and 16% were on Twitter. For sampled scholars' publications, social
reference manager bookmarks were compared to Scopus and Web of Science
citations; we found that Mendeley covers more than 80% of sampled articles, and
that Mendeley bookmarks are significantly correlated (r=.45) to Scopus citation
counts.
|
1205.5614
|
Performance Analysis of Optimal Single Stream Beamforming in MIMO
Dual-Hop AF Systems
|
cs.IT math.IT
|
This paper investigates the performance of optimal single stream beamforming
schemes in multiple-input multiple-output (MIMO) dual-hop amplify-and-forward
(AF) systems. Assuming channel state information is not available at the source
and relay, the optimal transmit and receive beamforming vectors are computed at
the destination, and the transmit beamforming vector is sent to the transmitter
via a dedicated feedback link. Then, a set of new closed-form expressions for
the statistical properties of the maximum eigenvalue of the resultant channel
is derived, i.e., the cumulative density function (cdf), probability density
function (pdf) and general moments, as well as the first order asymptotic
expansion and asymptotic large dimension approximations. These analytical
expressions are then applied to study three important performance metrics of
the system, i.e., outage probability, average symbol error rate and ergodic
capacity. In addition, more detailed treatments are provided for some important
special cases, e.g., when the number of antennas at one of the nodes is one or
large, simple and insightful expressions for the key parameters such as
diversity order and array gain of the system are derived. With the analytical
results, the joint impact of source, relay and destination antenna numbers on
the system performance is addressed, and the performance of optimal beamforming
schemes and orthogonal space-time block-coding (OSTBC) schemes are compared.
Results reveal that the number of antennas at the relay has a great impact on
how the numbers of antennas at the source and destination contribute to the
system performance, and optimal beamforming not only achieves the same maximum
diversity order as OSTBC, but also provides significant power gains over OSTBC.
|
1205.5632
|
Quantum contextuality in classical information retrieval
|
cs.IR
|
Document ranking based on probabilistic evaluations of relevance is known to
exhibit non-classical correlations, which may be explained by admitting a
complex structure of the event space, namely, by assuming the events to emerge
from multiple sample spaces. The structure of event space formed by overlapping
sample spaces is known in quantum mechanics, they may exhibit some
counter-intuitive features, called quantum contextuality. In this Note I
observe that from the structural point of view quantum contextuality looks
similar to personalization of information retrieval scenarios. Along these
lines, Knowledge Revision is treated as operationalistic measurement and a way
to quantify the rate of personalization of Information Retrieval scenarios is
suggested.
|
1205.5649
|
Transmission Capacity of Wireless Ad Hoc Networks with Energy Harvesting
Nodes
|
cs.IT math.IT
|
Transmission capacity of an ad hoc wireless network is analyzed when each
node of the network harvests energy from nature, e.g. solar, wind, vibration
etc. Transmission capacity is the maximum allowable density of nodes,
satisfying a per transmitter-receiver rate, and an outage probability
constraint. Energy arrivals at each node are assumed to follow a Bernoulli
distribution, and each node stores energy using an energy buffer/battery. For
ALOHA medium access protocol (MAP), optimal transmission probability that
maximizes the transmission capacity is derived as a function of the energy
arrival distribution. Game theoretic analysis is also presented for ALOHA MAP,
where each transmitter tries to maximize its own throughput, and symmetric Nash
equilibrium is derived. For CSMA MAP, back-off probability and outage
probability are derived in terms of input energy distribution, thereby
characterizing the transmission capacity.
|
1205.5651
|
Measuring the evolution of contemporary western popular music
|
cs.SD cs.IR cs.MM physics.soc-ph stat.AP
|
Popular music is a key cultural expression that has captured listeners'
attention for ages. Many of the structural regularities underlying musical
discourse are yet to be discovered and, accordingly, their historical evolution
remains formally unknown. Here we unveil a number of patterns and metrics
characterizing the generic usage of primary musical facets such as pitch,
timbre, and loudness in contemporary western popular music. Many of these
patterns and metrics have been consistently stable for a period of more than
fifty years, thus pointing towards a great degree of conventionalism.
Nonetheless, we prove important changes or trends related to the restriction of
pitch transitions, the homogenization of the timbral palette, and the growing
loudness levels. This suggests that our perception of the new would be rooted
on these changing characteristics. Hence, an old tune could perfectly sound
novel and fashionable, provided that it consisted of common harmonic
progressions, changed the instrumentation, and increased the average loudness.
|
1205.5662
|
Google+ or Google-?: Dissecting the Evolution of the New OSN in its
First Year
|
cs.SI cs.NI
|
In the era when Facebook and Twitter dominate the market for social media,
Google has introduced Google+ (G+) and reported a significant growth in its
size while others called it a ghost town. This begs the question that "whether
G+ can really attract a significant number of connected and active users
despite the dominance of Facebook and Twitter?".
This paper tackles the above question by presenting a detailed
characterization of G+ based on large scale measurements. We identify the main
components of G+ structure, characterize the key features of their users and
their evolution over time. We then conduct detailed analysis on the evolution
of connectivity and activity among users in the largest connected component
(LCC) of G+ structure, and compare their characteristics with other major OSNs.
We show that despite the dramatic growth in the size of G+, the relative size
of LCC has been decreasing and its connectivity has become less clustered.
While the aggregate user activity has gradually increased, only a very small
fraction of users exhibit any type of activity. To our knowledge, our study
offers the most comprehensive characterization of G+ based on the largest
collected data sets.
|
1205.5699
|
Minimal Binary Abelian Codes of length $p^m q^n$
|
cs.IT math.IT
|
We consider binary abelian codes of length $p^m q^n$, where $p$ and $q$ are
prime rational integers under some restrictive hypotheses. In this case, we
determine the idempotents generating minimal codes and either the respective
weights or bounds of these weights. We give examples showing that these bounds
are attained in some cases.
|
1205.5720
|
Tie-RBAC: An application of RBAC to Social Networks
|
cs.SI cs.CR
|
This paper explores the application of role-based access control to social
networks, from the perspective of social network analysis. Each tie, composed
of a relation, a sender and a receiver, involves the sender's assignation of
the receiver to a role with permissions. The model is not constrained to
system-defined relations and lets users define them unilaterally. It benefits
of RBAC's advantages, such as policy neutrality, simplification of security
administration and permissions on other roles. Tie-RBAC has been implemented in
a core for building social network sites, Social Stream.
|
1205.5729
|
Blind Reconciliation
|
quant-ph cs.IT math.IT
|
Information reconciliation is a crucial procedure in the classical
post-processing of quantum key distribution (QKD). Poor reconciliation
efficiency, revealing more information than strictly needed, may compromise the
maximum attainable distance, while poor performance of the algorithm limits the
practical throughput in a QKD device. Historically, reconciliation has been
mainly done using close to minimal information disclosure but heavily
interactive procedures, like Cascade, or using less efficient but also less
interactive -just one message is exchanged- procedures, like the ones based in
low-density parity-check (LDPC) codes. The price to pay in the LDPC case is
that good efficiency is only attained for very long codes and in a very narrow
range centered around the quantum bit error rate (QBER) that the code was
designed to reconcile, thus forcing to have several codes if a broad range of
QBER needs to be catered for. Real world implementations of these methods are
thus very demanding, either on computational or communication resources or
both, to the extent that the last generation of GHz clocked QKD systems are
finding a bottleneck in the classical part. In order to produce compact, high
performance and reliable QKD systems it would be highly desirable to remove
these problems. Here we analyse the use of short-length LDPC codes in the
information reconciliation context using a low interactivity, blind, protocol
that avoids an a priori error rate estimation. We demonstrate that 2x10^3 bits
length LDPC codes are suitable for blind reconciliation. Such codes are of high
interest in practice, since they can be used for hardware implementations with
very high throughput.
|
1205.5742
|
Implementation of an Onboard Visual Tracking System with Small Unmanned
Aerial Vehicle (UAV)
|
cs.RO
|
This paper presents a visual tracking system that is capable or running real
time on-board a small UAV (Unmanned Aerial Vehicle). The tracking system is
computationally efficient and invariant to lighting changes and rotation of the
object or the camera. Detection and tracking is autonomously carried out on the
payload computer and there are two different methods for creation of the image
patches. The first method starts detecting and tracking using a stored image
patch created prior to flight with previous flight data. The second method
allows the operator on the ground to select the interest object for the UAV to
track. The tracking system is capable of re-detecting the object of interest in
the events of tracking failure. Performance of the tracking system was verified
both in the lab and during actual flights of the UAV. Results show that the
system can run on-board and track a diverse set of objects in real time.
|
1205.5745
|
Generic Expression Hardness Results for Primitive Positive Formula
Comparison
|
cs.LO cs.CC cs.DB
|
We study the expression complexity of two basic problems involving the
comparison of primitive positive formulas: equivalence and containment. In
particular, we study the complexity of these problems relative to finite
relational structures. We present two generic hardness results for the studied
problems, and discuss evidence that they are optimal and yield, for each of the
problems, a complexity trichotomy.
|
1205.5819
|
Measurability Aspects of the Compactness Theorem for Sample Compression
Schemes
|
stat.ML cs.LG
|
It was proved in 1998 by Ben-David and Litman that a concept space has a
sample compression scheme of size d if and only if every finite subspace has a
sample compression scheme of size d. In the compactness theorem, measurability
of the hypotheses of the created sample compression scheme is not guaranteed;
at the same time measurability of the hypotheses is a necessary condition for
learnability. In this thesis we discuss when a sample compression scheme,
created from com- pression schemes on finite subspaces via the compactness
theorem, have measurable hypotheses. We show that if X is a standard Borel
space with a d-maximum and universally separable concept class C, then (X,C)
has a sample compression scheme of size d with universally Borel measurable
hypotheses. Additionally we introduce a new variant of compression scheme
called a copy sample compression scheme.
|
1205.5823
|
Foreword: A Computable Universe, Understanding Computation and Exploring
Nature As Computation
|
cs.GL cs.AI cs.CC cs.IT math.IT physics.hist-ph physics.pop-ph
|
I am most honoured to have the privilege to present the Foreword to this
fascinating and wonderfully varied collection of contributions, concerning the
nature of computation and of its deep connection with the operation of those
basic laws, known or yet unknown, governing the universe in which we live.
Fundamentally deep questions are indeed being grappled with here, and the fact
that we find so many different viewpoints is something to be expected, since,
in truth, we know little about the foundational nature and origins of these
basic laws, despite the immense precision that we so often find revealed in
them. Accordingly, it is not surprising that within the viewpoints expressed
here is some unabashed speculation, occasionally bordering on just partially
justified guesswork, while elsewhere we find a good deal of precise reasoning,
some in the form of rigorous mathematical theorems. Both of these are as should
be, for without some inspired guesswork we cannot have new ideas as to where
look in order to make genuinely new progress, and without precise mathematical
reasoning, no less than in precise observation, we cannot know when we are
right -- or, more usually, when we are wrong.
|
1205.5849
|
Multi-Cell Random Beamforming: Achievable Rate and Degrees of Freedom
Region
|
cs.IT math.IT
|
Random beamforming (RBF) is a practically favourable transmission scheme for
multiuser multi-antenna downlink systems since it requires only partial channel
state information (CSI) at the transmitter. Under the conventional single-cell
setup, RBF is known to achieve the optimal sum-capacity scaling law as the
number of users goes to infinity, thanks to the multiuser diversity enabled
transmission scheduling that virtually eliminates the intra-cell interference.
In this paper, we extend the study of RBF to a more practical multi-cell
downlink system with single-antenna receivers subject to the additional
inter-cell interference (ICI). First, we consider the case of finite
signal-to-noise ratio (SNR) at each receiver. We derive a closed-form
expression of the achievable sum-rate with the multi-cell RBF, based upon which
we show an asymptotic sum-rate scaling law as the number of users goes to
infinity. Next, we consider the high-SNR regime and for tractable analysis
assume that the number of users in each cell scales in a certain order with the
per-cell SNR. Under this setup, we characterize the achievable degrees of
freedom (DoF) for the single-cell case with RBF. Then we extend the analysis to
the multi-cell RBF case by characterizing the DoF region. It is shown that the
DoF region characterization provides useful guideline on how to design a
cooperative multi-cell RBF system to achieve optimal throughput tradeoffs among
different cells. Furthermore, our results reveal that the multi-cell RBF scheme
achieves the "interference-free DoF" region upper bound for the multi-cell
system, provided that the per-cell number of users has a sufficiently large
scaling order with the SNR. Our result thus confirms the optimality of
multi-cell RBF in this regime even without the complete CSI at the transmitter,
as compared to other full-CSI requiring transmission schemes such as
interference alignment.
|
1205.5856
|
Nearest-neighbor Entropy Estimators with Weak Metrics
|
cs.IT math.IT math.ST stat.TH
|
A problem of improving the accuracy of nonparametric entropy estimation for a
stationary ergodic process is considered. New weak metrics are introduced and
relations between metrics, measures, and entropy are discussed. Based on weak
metrics, a new nearest-neighbor entropy estimator is constructed and has a
parameter with which the estimator is optimized to reduce its bias. It is shown
that estimator's variance is upper-bounded by a nearly optimal Cramer-Rao lower
bound.
|
1205.5863
|
Construction of LDGM lattices
|
cs.IT cs.CR math.CO math.IT
|
Low density generator matrix (LDGM) codes have an acceptable performance
under iterative decoding algorithms. This idea is used to construct a class of
lattices with relatively good performance and low encoding and decoding
complexity. To construct such lattices, Construction D is applied to a set of
generator vectors of a class of LDGM codes. Bounds on the minimum distance and
the coding gain of the corresponding lattices and a corollary for the cross
sections and projections of these lattices are provided. The progressive edge
growth (PEG) algorithm is used to construct a class of binary codes to generate
the corresponding lattice. Simulation results confirm the acceptable
performance of these class of lattices.
|
1205.5866
|
Approximate Equalities on Rough Intuitionistic Fuzzy Sets and an
Analysis of Approximate Equalities
|
cs.AI
|
In order to involve user knowledge in determining equality of sets, which may
not be equal in the mathematical sense, three types of approximate (rough)
equalities were introduced by Novotny and Pawlak ([8, 9, 10]). These notions
were generalized by Tripathy, Mitra and Ojha ([13]), who introduced the
concepts of approximate (rough) equivalences of sets. Rough equivalences
capture equality of sets at a higher level than rough equalities. More
properties of these concepts were established in [14]. Combining the conditions
for the two types of approximate equalities, two more approximate equalities
were introduced by Tripathy [12] and a comparative analysis of their relative
efficiency was provided. In [15], the four types of approximate equalities were
extended by considering rough fuzzy sets instead of only rough sets. In fact
the concepts of leveled approximate equalities were introduced and properties
were studied. In this paper we proceed further by introducing and studying the
approximate equalities based on rough intuitionistic fuzzy sets instead of
rough fuzzy sets. That is we introduce the concepts of approximate
(rough)equalities of intuitionistic fuzzy sets and study their properties. We
provide some real life examples to show the applications of rough equalities of
fuzzy sets and rough equalities of intuitionistic fuzzy sets.
|
1205.5904
|
Joint Compute and Forward for the Two Way Relay Channel with Spatially
Coupled LDPC Codes
|
cs.IT math.IT
|
We consider the design and analysis of coding schemes for the binary input
two way relay channel with erasure noise. We are particularly interested in
reliable physical layer network coding in which the relay performs perfect
error correction prior to forwarding messages. The best known achievable rates
for this problem can be achieved through either decode and forward or compute
and forward relaying. We consider a decoding paradigm called joint compute and
forward which we numerically show can achieve the best of these rates with a
single encoder and decoder. This is accomplished by deriving the exact
performance of a message passing decoder based on joint compute and forward for
spatially coupled LDPC ensembles.
|
1205.5906
|
Channel-aware Decentralized Detection via Level-triggered Sampling
|
stat.AP cs.IT math.IT
|
We consider decentralized detection through distributed sensors that perform
level-triggered sampling and communicate with a fusion center via noisy
channels. Each sensor computes its local log-likelihood ratio (LLR), samples it
using the level-triggered sampling, and upon sampling transmits a single bit to
the FC. Upon receiving a bit from a sensor, the FC updates the global LLR and
performs a sequential probability ratio test (SPRT) step. We derive the fusion
rules under various types of channels. We further provide an asymptotic
analysis on the average detection delay for the proposed channel-aware scheme,
and show that the asymptotic detection delay is characterized by a KL
information number. The delay analysis facilitates the choice of appropriate
signaling schemes under different channel types for sending the 1-bit
information from sensors to the FC.
|
1205.5914
|
Constructive spherical codes on layers of flat tori
|
cs.IT math.IT
|
A new class of spherical codes is constructed by selecting a finite subset of
flat tori from a foliation of the unit sphere S^{2L-1} of R^{2L} and designing
a structured codebook on each torus layer. The resulting spherical code can be
the image of a lattice restricted to a specific hyperbox in R^L in each layer.
Group structure and homogeneity, useful for efficient storage and decoding, are
inherited from the underlying lattice codebook. A systematic method for
constructing such codes are presented and, as an example, the Leech lattice is
used to construct a spherical code in R^{48}. Upper and lower bounds on the
performance, the asymptotic packing density and a method for decoding are
derived.
|
1205.5921
|
Diabetes prediction using Machine Learning algorithms and ontology
|
cs.DB
|
Diabetes is one of the chronic diseases, which is increasing from year to
year. The problems begin when diabetes is not detected at an early phase and
diagnosed properly at the appropriate time. Different machine learning
techniques, as well as ontology-based ML techniques, have recently played an
important role in medical science by developing an automated system that can
detect diabetes patients. This paper provides a comparative study and review of
the most popular machine learning techniques and ontology-based Machine
Learning classification. Various types of classification algorithms were
considered namely: SVM, KNN, ANN, Naive Bayes, Logistic regression, and
Decision Tree. The results are evaluated based on performance metrics like
Recall, Accuracy, Precision, and F-Measure that are derived from the confusion
matrix. The experimental results showed that the best accuracy goes for
ontology classifiers and SVM.
|
1205.5922
|
Discovering new technique for mapping relational database based on
semantic web technology
|
cs.DB
|
Most of data on the Web are still stored in relational databases. Therefore,
it is more important to make the correspondence between relational databases
(RDB) and ontologies for storing the Web data. In this paper, we present an new
approach to map the data stored in relational databases into the Semantic Web,
we exploit simple mappings based on some specifications of the database schema,
and we explain how relational databases can be used to define a mapping
mechanism between relational database and OWL ontology. A framework has been
developed, which migrates successfully RDB into OWL document. The experimental
results were very important, demonstrating that the proposed method is feasible
and efficient.
|
1205.5923
|
Integration of ontology with machine learning to predict the presence of
covid-19 based on symptoms
|
cs.IR
|
Coronavirus (covid 19) is one of the most dangerous viruses that have spread
all over the world. With the increasing number of cases infected with the
coronavirus, it has become necessary to address this epidemic by all available
means. Detection of the covid-19 is currently one of the world's most difficult
challenges. Data science and machine learning (ML), for example, can aid in the
battle against this pandemic. Furthermore, various research published in this
direction proves that ML techniques can identify illness and viral infections
more precisely, allowing patients' diseases to be detected at an earlier stage.
In this paper, we will present how ontologies can aid in predicting the
presence of covid-19 based on symptoms. The integration of ontology and ML is
achieved by implementing rules of the decision tree algorithm into ontology
reasoner. In addition, we compared the outcomes with various ML classifications
used to make predictions. The findings are assessed using performance measures
generated from the confusion matrix, such as F-measure, accuracy, precision,
and recall. The ontology surpassed all ML algorithms with high accuracy value
of 97.4%, according to the results.
|
1205.5925
|
Multiple Random Walks to Uncover Short Paths in Power Law Networks
|
cs.SI physics.soc-ph
|
Consider the following routing problem in the context of a large scale
network $G$, with particular interest paid to power law networks, although our
results do not assume a particular degree distribution. A small number of nodes
want to exchange messages and are looking for short paths on $G$. These nodes
do not have access to the topology of $G$ but are allowed to crawl the network
within a limited budget. Only crawlers whose sample paths cross are allowed to
exchange topological information. In this work we study the use of random walks
(RWs) to crawl $G$. We show that the ability of RWs to find short paths bears
no relation to the paths that they take. Instead, it relies on two properties
of RWs on power law networks: 1) RW's ability observe a sizable fraction of the
network edges; and 2) an almost certainty that two distinct RW sample paths
cross after a small percentage of the nodes have been visited. We show
promising simulation results on several real world networks.
|
1205.5927
|
An Approximate Projected Consensus Algorithm for Computing Intersection
of Convex Sets
|
cs.SY math.OC
|
In this paper, we propose an approximate projected consensus algorithm for a
network to cooperatively compute the intersection of convex sets. Instead of
assuming the exact convex projection proposed in the literature, we allow each
node to compute an approximate projection and communicate it to its neighbors.
The communication graph is directed and time-varying. Nodes update their states
by weighted averaging. Projection accuracy conditions are presented for the
considered algorithm. They indicate how much projection accuracy is required to
ensure global consensus to a point in the intersection set when the
communication graph is uniformly jointly strongly connected. We show that
$\pi/4$ is a critical angle error of the projection approximation to ensure a
bounded state. A numerical example indicates that this approximate projected
consensus algorithm may achieve better performance than the exact projected
consensus algorithm in some cases.
|
1205.5938
|
Distributed Traffic Signal Control for Maximum Network Throughput
|
cs.SY
|
We propose a distributed algorithm for controlling traffic signals. Our
algorithm is adapted from backpressure routing, which has been mainly applied
to communication and power networks. We formally prove that our algorithm
ensures global optimality as it leads to maximum network throughput even though
the controller is constructed and implemented in a completely distributed
manner. Simulation results show that our algorithm significantly outperforms
SCATS, an adaptive traffic signal control system that is being used in many
cities.
|
1205.5959
|
On the Cross-Correlation of a $p$-ary m-Sequence and its Decimated
Sequences by $d=\frac{p^n+1}{p^k+1}+\frac{p^n-1}{2}$
|
cs.IT math.IT math.NT
|
In this paper, for an odd prime $p$ such that $p\equiv 3\bmod 4$, odd $n$,
and $d=(p^n+1)/(p^k+1)+(p^n-1)/2$ with $k|n$, the value distribution of the
exponential sum $S(a,b)$ is calculated as $a$ and $b$ run through
$\mathbb{F}_{p^n}$. The sequence family $\mathcal{G}$ in which each sequence
has the period of $N=p^n-1$ is also constructed. The family size of
$\mathcal{G}$ is $p^n$ and the correlation magnitude is roughly upper bounded
by $(p^k+1)\sqrt{N}/2$. The weight distribution of the relevant cyclic code
$\mathcal{C}$ over $\mathbb{F}_p$ with the length $N$ and the dimension ${\rm
dim}_{\mathbb{F}_p}\mathcal{C}=2n$ is also derived. Our result includes the
case in \cite{Xia} as a special case.
|
1205.5979
|
Achievable Rate Regions for the Dirty Multiple Access Channel with
Partial Side Information at the Transmitters
|
cs.IT math.IT
|
In this paper, we establish achievable rate regions for the multiple access
channel (MAC) with side information partially known (estimated or sensed
version) at the transmitters. Actually, we extend the lattice strategies used
by Philosof-Zamir for the MAC with full side information at the transmitters to
the partially known case. We show that the sensed or estimated side information
reduces the rate regions, the same as that occurs for Costa Gaussian channel.
|
1205.5980
|
Performance of polar codes for quantum and private classical
communication
|
quant-ph cs.IT math.IT
|
We analyze the practical performance of quantum polar codes, by computing
rigorous bounds on block error probability and by numerically simulating them.
We evaluate our bounds for quantum erasure channels with coding block lengths
between 2^10 and 2^20, and we report the results of simulations for quantum
erasure channels, quantum depolarizing channels, and "BB84" channels with
coding block lengths up to N = 1024. For quantum erasure channels, we observe
that high quantum data rates can be achieved for block error rates less than
10^(-4) and that somewhat lower quantum data rates can be achieved for quantum
depolarizing and BB84 channels. Our results here also serve as bounds for and
simulations of private classical data transmission over these channels,
essentially due to Renes' duality bounds for privacy amplification and
classical data transmission of complementary observables. Future work might be
able to improve upon our numerical results for quantum depolarizing and BB84
channels by employing a polar coding rule other than the heuristic used here.
|
1205.6010
|
The Chromatin Organization of an Eukaryotic Genome : Sequence Specific+
Statistical=Combinatorial (Extended Abstract)
|
q-bio.GN cs.CE
|
Nucleosome organization in eukaryotic genomes has a deep impact on gene
function. Although progress has been recently made in the identification of
various concurring factors influencing nucleosome positioning, it is still
unclear whether nucleosome positions are sequence dictated or determined by a
random process. It has been postulated for a long time that,in the proximity of
TSS, a barrier determines the position of the +1 nucleosome and then geometric
constraints alter the random positioning process determining nucleosomal
phasing. Such a pattern fades out as one moves away from the barrier to become
again a random positioning process. Although this statistical model is widely
accepted,the molecular nature of the barrier is still unknown. Moreover,we are
far from the identification of a set of sequence rules able:to account for the
genome-wide nucleosome organization;to explain the nature of the barriers on
which the statistical mechanism hinges;to allow for a smooth transition from
sequence-dictated to statistical positioning and back. We show that sequence
complexity,quantified via various methods, can be the rule able to at least
partially account for all the above.In particular, we have conducted our
analyses on 4 high resolution nucleosomal maps of the model eukaryotes and
found that nucleosome depleted regions can be well distinguished from
nucleosome enriched regions by sequence complexity measures.In particular, (a)
the depleted regions are less complex than the enriched ones, (b) around TSS
complexity measures alone are in striking agreement with in vivo nucleosome
occupancy,in particular precisely indicating the positions of the +1 and -1
nucleosomes. Those findings indicate that the intrinsic richness of
subsequences within sequences plays a role in nucleosomal formation in genomes,
and that sequence complexity constitutes the molecular nature of nucleosome
barrier.
|
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